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Related Concept Videos

Kaplan-Meier Approach01:24

Kaplan-Meier Approach

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The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
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Designing and plotting a curve using field data requires precise calculations and execution. A horizontal curve with a radius of 200 meters and an intersection angle of 20 degrees is established using the method of perpendicular offsets from the long chord. The long chord, which spans between the curve's endpoints, is calculated to be 69.46 meters in length. To maintain accuracy in plotting, intervals of 3 meters are selected along the chord.The engineer determines the offset distances for each...
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Synaptic integration mainly includes the summation of graded potentials. Graded potentials, regardless of their type, cause subtle alterations in membrane voltage, resulting in either depolarization or hyperpolarization. These incremental changes, when combined or summed, can propel the neuron toward its threshold. Consider, for example, a membrane experiencing a +15 mV shift, causing it to depolarize from -70 mV to -55 mV. In this scenario, graded potentials govern the membrane's ability to...
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A titration curve is a plot of some solution property versus the amount of added titrant. For acid-base titrations, solution pH is a useful property to monitor because it varies predictably with the solution composition and, therefore, may be used to monitor the titration’s progress and detect its endpoint. Acid-base titration can be performed with a strong acid and a strong base, a strong acid and a weak base, or a strong base and a weak acid.
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Survival curves are graphical representations that depict the survival experience of a population over time, offering an intuitive way to track the proportion of individuals who remain event-free at each time point. These curves are widely used in fields such as medicine, public health, and reliability engineering to visualize and compare survival probabilities across different groups or conditions.
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Establishing a Competing Risk Regression Nomogram Model for Survival Data
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Reconstructing time-to-event data from published Kaplan-Meier curves.

Yinghui Wei1, Patrick Royston2

  • 1Centre for Mathematical Sciences, School of Computing, Electronics, and Mathematics, Plymouth University, Plymouth, UK.

The Stata Journal
|February 6, 2018
PubMed
Summary
This summary is machine-generated.

Researchers can now convert Kaplan-Meier curves into individual-level time-to-event data. This new method reconstructs data, offering more than just hazard ratio approximation for survival analysis.

Keywords:
Kaplan–Meier curveshazard ratiosipdfcst0498time-to-event data

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Area of Science:

  • Biostatistics
  • Survival Analysis
  • Medical Informatics

Background:

  • Kaplan-Meier curves are widely used in survival analysis to estimate survival probabilities over time.
  • Extracting individual-level data from published Kaplan-Meier curves has been a challenge.
  • Existing methods primarily focus on approximating hazard ratios.

Purpose of the Study:

  • To introduce a new command, ipdfc, for reconstructing time-to-event data from Kaplan-Meier curves.
  • To extend the utility of Kaplan-Meier curves beyond hazard ratio estimation.
  • To facilitate the generation of individual-level survival data.

Main Methods:

  • The study introduces the 'ipdfc' command.
  • This command implements a reconstruction method to convert graphical Kaplan-Meier curve data into a dataset of individual time-to-event observations.
  • The method leverages data points extracted from published survival curves.

Main Results:

  • The 'ipdfc' command successfully reconstructs time-to-event data from Kaplan-Meier curves.
  • The generated data can be used for various downstream survival analyses at the individual level.
  • Examples demonstrate the practical application and ease of use of the command.

Conclusions:

  • The 'ipdfc' command provides a valuable tool for researchers working with survival data.
  • It enables the derivation of individual-level data from published Kaplan-Meier curves, enhancing data usability.
  • This method expands the analytical possibilities for studies relying on published survival data.