Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Hazard Rate01:11

Hazard Rate

The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
Prediction Intervals01:03

Prediction Intervals

The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
The...
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
Relative Risk01:12

Relative Risk

Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Risk, Predictors, and Outcomes of Acute Kidney Injury in Patients Admitted to Intensive Care Units in Egypt.

Scientific reports·2017
Same author

Long-Term Progression of Coronary Artery Calcification Is Independent of Classical Risk Factors, C-Reactive Protein, and Parathyroid Hormone in Renal Transplant Patients.

Cardiorenal medicine·2017
Same author

Obesity and kidney disease: Hidden consequences of the epidemic.

African journal of primary health care & family medicine·2017
Same author

Validation of echocardiographic criteria for the clinical diagnosis of heart failure in chronic kidney disease.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association·2017
Same author

Optimizing hypertension management in renal transplantation: a call to action.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association·2017
Same author

Optimizing hypertension management in renal transplantation: a call to action.

Journal of hypertension·2017
Same journal

Effect of Semaglutide on Measured vs Estimated Glomerular Filtration Rate.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association·2026
Same journal

Beyond Diffusion and Convection: Is Adsorption the Third Dimension of Dialysis?

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association·2026
Same journal

Pivotal Clinical Trials in C3 Glomerulopathy: answers and remaining uncertainties.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association·2026
Same journal

Urinary protein vs albumin for assessing kidney failure risk in chronic kidney disease.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association·2026
Same journal

Systolic blood pressure and albuminuria reduction mediate cardiovascular benefits of finerenone in T2 diabetes and CKD.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association·2026
Same journal

Bortezomib-Cyclophosphamide-Dexamethasone versus Rituximab in PGNMID.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association·2026
See all related articles

Related Experiment Video

Updated: May 11, 2026

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

Risk prediction models.

Giovanni Tripepi1, Georg Heinze, Kitty J Jager

  • 1CNR-IBIM, Clinical Epidemiology and Physiopathology of Renal Diseases and Hypertension of Reggio Calabria, Calabria, Italy.

Nephrology, Dialysis, Transplantation : Official Publication of the European Dialysis and Transplant Association - European Renal Association
|May 10, 2013
PubMed
Summary
This summary is machine-generated.

This study explains how to develop and validate risk prediction models for diseases like coronary heart disease (CHD) and chronic kidney disease (CKD). Proper validation ensures accurate prognostication for better clinical decision-making.

Keywords:
prognostic researchrisk calculatorsrisk prediction model

More Related Videos

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

Related Experiment Videos

Last Updated: May 11, 2026

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

Area of Science:

  • Medical research
  • Clinical epidemiology
  • Biostatistics

Background:

  • Prognostic research predicts disease outcomes using probability.
  • Risk prediction models estimate event probability based on patient factors.
  • Validated models are crucial for clinical decision-making.

Purpose of the Study:

  • To discuss the development and validation of risk prediction models.
  • To illustrate these concepts using examples of coronary heart disease and chronic kidney disease.
  • To highlight the importance of model validation for clinical application.

Main Methods:

  • Review of prognostic research concepts.
  • Explanation of risk prediction model development and validation.
  • Illustrative examples: Framingham risk calculator (CHD) and Renal Risk Score (CKD).
  • Discussion of discrimination, calibration, and reclassification analyses.

Main Results:

  • Risk prediction models require rigorous validation (discrimination, calibration).
  • Reclassification analyses assess improvements over existing models.
  • The Framingham risk calculator and Renal Risk Score serve as practical examples.
  • Validated models enhance clinical decision-making for diseases like CHD and CKD.

Conclusions:

  • Accurate prognostication relies on well-developed and validated risk prediction models.
  • Model validation is essential before clinical implementation.
  • These models aid in estimating patient-specific event probabilities and guiding treatment.