R Dataset / Package survival / mgus

How To Create a Barplot

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How To Create a Stacked Barplot

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How To Create a Pie Chart

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How To Compute the Mean

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How To Create a Plot

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How to Compute the Median

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Boxplot

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Correlation Coefficient

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Cumulative Frequency Histogram

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Dotplot

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Hollow Histogram

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Numerical Summaries

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Pie Chart

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Plot

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Ratio

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Regression

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Stem and Leaf Plots

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Visual Summaries

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Submitted by pmagunia on March 9, 2018 - 1:06 PM
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Attachment Size
dataset-62816.csv 11.22 KB
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Documentation

On this Picostat.com statistics page, you will find information about the mgus data set which pertains to Monoclonal gammapothy data. The mgus data set is found in the survival R package. Try to load the mgus data set in R by issuing the following command at the console data("mgus"). This may load the data into a variable called mgus. If R says the mgus data set is not found, you can try installing the package by issuing this command install.packages("survival") and then attempt to reload the data with library("survival") followed by data("mgus"). Perhaps strangley, if R gives you no output after entering a command, it means the command succeeded. If it succeeded you can see the data by typing mgus at the command-line which should display the entire dataset.

If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the mgus R data set. The size of this file is about 11,493 bytes.


Monoclonal gammapothy data

Description

Natural history of 241 subjects with monoclonal gammapothy of undetermined significance (MGUS).

Usage

mgus
mgus1

Format

mgus: A data frame with 241 observations on the following 12 variables.

id: subject id
age: age in years at the detection of MGUS
sex: male or female
dxyr: year of diagnosis
pcdx: for subjects who progress to a plasma cell malignancy
the subtype of malignancy: multiple myeloma (MM) is the
most common, followed by amyloidosis (AM), macroglobulinemia (MA),
and other lymphprolifative disorders (LP)
pctime: days from MGUS until diagnosis of a plasma cell malignancy
futime: days from diagnosis to last follow-up
death: 1= follow-up is until death
alb: albumin level at MGUS diagnosis
creat: creatinine at MGUS diagnosis
hgb: hemoglobin at MGUS diagnosis
mspike: size of the monoclonal protein spike at diagnosis

mgus1: The same data set in start,stop format. Contains the id, age, sex, and laboratory variable described above along with

start, stop: sequential intervals of time for each subject
status: =1 if the interval ends in an event
event: a factor containing the event type: censor, death, or plasma cell malignancy
enum: event number for each subject: 1 or 2

Details

Plasma cells are responsible for manufacturing immunoglobulins, an important part of the immune defense. At any given time there are estimated to be about 10^6 different immunoglobulins in the circulation at any one time. When a patient has a plasma cell malignancy the distribution will become dominated by a single isotype, the product of the malignant clone, visible as a spike on a serum protein electrophoresis. Monoclonal gammapothy of undertermined significance (MGUS) is the presence of such a spike, but in a patient with no evidence of overt malignancy. This data set of 241 sequential subjects at Mayo Clinic was the groundbreaking study defining the natural history of such subjects. Due to the diligence of the principle investigator 0 subjects have been lost to follow-up.

Three subjects had MGUS detected on the day of death. In data set mgus1 these subjects have the time to MGUS coded as .5 day before the death in order to avoid tied times.

These data sets were updated in Jan 2015 to correct some small errors.

Source

Mayo Clinic data courtesy of Dr. Robert Kyle.

References

R Kyle, Benign monoclonal gammopathy – after 20 to 35 years of follow-up, Mayo Clinic Proc 1993; 68:26-36.

Examples

# Create the competing risk curves for time to first of death or PCM
sfit <- survfit(Surv(start, stop, event) ~ sex, mgus1, subset=(enum==1))
print(sfit)  # the order of printout is the order in which they plotplot(sfit, xscale=365.25, lty=c(2,1,2,1), col=c(1,1,2,2),
     xlab="Years after MGUS detection", ylab="Proportion")
legend(0, .8, c("Death/male", "Death/female", "PCM/male", "PCM/female"),
       lty=c(1,1,2,2), col=c(2,1,2,1), bty='n')title("Curves for the first of plasma cell malignancy or death")
# The plot shows that males have a higher death rate than females (no
# surprise) but their rates of conversion to PCM are essentially the same.

--

Dataset imported from https://www.r-project.org.
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