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Related Concept Videos

Hazard Rate01:11

Hazard Rate

238
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...
238
Hazard Ratio01:12

Hazard Ratio

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The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
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Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

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Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
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The Mantel-Cox Log-Rank Test01:19

The Mantel-Cox Log-Rank Test

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The Mantel-Cox log-rank test is a widely used statistical method for comparing the survival distributions of two groups. It tests whether a statistically significant difference exists in survival times between the groups without assuming a specific distribution for the survival data, making it a non-parametric test. This flexibility makes the log-rank test particularly valuable in medical research and other fields where the timing of an event, such as death or disease recurrence, is of...
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Relative Risk01:12

Relative Risk

658
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...
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Odds Ratio01:09

Odds Ratio

495
The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
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Establishing a Competing Risk Regression Nomogram Model for Survival Data
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Estimating the hazard rate difference from case-cohort studies.

Jie K Hu1, Kwun C G Chan2, David J Couper3

  • 1Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA. contact@katehu.com.

European Journal of Epidemiology
|June 14, 2021
PubMed
Summary
This summary is machine-generated.

A new R package, addhazard, enables additive hazards models for case-cohort studies, improving coronary heart disease risk prediction using biomarkers high-sensitivity C-reactive protein (hs-CRP) and Lipoprotein-associated phospholipase A2 (Lp-PLA2). Auxiliary data enhances precision, revealing synergistic biomarker effects.

Keywords:
Additive hazards modelsAuxiliary variablesCase cohort studyHazard differenceLp-PLA2hs-CRP

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Cardiovascular Disease Research

Background:

  • Case-cohort studies offer cost-effective epidemiological research by sampling informative participants for expensive measurements.
  • Additive hazards models, estimating hazard differences, are underutilized in case-cohort studies due to software and application limitations.

Purpose of the Study:

  • To introduce a novel estimation method and R package (addhazard) for analyzing additive hazards models in general two-phase sampling studies, including case-cohort designs.
  • To demonstrate the application of this method in assessing coronary heart disease (CHD) risk associated with biomarkers high-sensitivity C-reactive protein (hs-CRP) and Lipoprotein-associated phospholipase A2 (Lp-PLA2).

Main Methods:

  • Developed an estimation method for additive hazards models applicable to two-phase sampling.
  • Implemented the method in the R package 'addhazard', supporting missing covariates, cohort stratification, robust variances, and auxiliary information.
  • Applied the method to the Atherosclerosis Risk in Communities Study data, analyzing hs-CRP and Lp-PLA2 in relation to CHD risk.

Main Results:

  • The 'addhazard' package facilitates the analysis of case-cohort studies using additive hazards models.
  • Incorporating auxiliary variables from the full cohort improved the precision of estimated hazard differences.
  • Synergistic effects of hs-CRP and Lp-PLA2 on CHD risk were observed, varying with LDL cholesterol levels, indicating potential for identifying high-risk individuals beyond traditional factors.

Conclusions:

  • The 'addhazard' R package provides a valuable tool for analyzing case-cohort studies with additive hazards models.
  • Auxiliary information from the full cohort can enhance the precision of epidemiological risk estimates.
  • Biomarkers hs-CRP and Lp-PLA2 show complex interactions influencing CHD risk, offering new avenues for risk stratification.