Name: Performing Restricted Mean Survival Time Analysis (RMST) Using SAS/STAT
Uploaded: 2019-10-06T23:30:13.000Z
Duration: 10 min 50 s
Description: Thousands of YouTube videos with English-Chinese subtitles! Now you can learn to understand native speakers, expand your vocabulary, and improve your pronunciation...

00:00:00,000 --> 00:00:02,910 Hello, my name is Changbin Guo.

I work for SAS R & D in statistical software

development, specializing in survival and event history

In this video I would like to talk to you

about some new features available in SAS/STAT 15.1 that

let you analyze the restricted mean survival time.

The LIFETEST and PHREG procedures in SAS/STAT software

The LIFETEST procedure focuses on nonparametric analysis,

for estimating the survival function and the log-rank test

focuses on regression modeling and supports the popular Cox

The proportional hazards, or PH, assumption

plays a fundamental role in both the log-rank test and the Cox

The log-rank test can be derived as a score test of the Cox

model and has the highest power when the assumption is true.

influences the performances of the log-rank test and the Cox

Unfortunately, however, non-proportional hazards

occurs when the two survival curves cross.

This implies that the corresponding hazard

functions would also cross and therefore violates

Because the log-rank statistic is essentially

a weighted sum of the hazard function over time,

the log-rank test can lose much of its power

to detect the true difference in survival.

When the true hazard ratio changes over time,

the estimated hazard ratio from the fitted model

ends up being a weighted average of the time-varying hazard

The problem is that the weights depend on the underlying

survival and censoring distributions and therefore

The restricted mean survival time, or RMST,

is defined as the expected value of the restricted survival time

The RMST is related to the survival mean.

When tau goes to infinity, the RMST becomes the survival mean.

For example, if the last observation is censored,

and when the survival does not drop below 0.5,

You can perform essentially the same types

To compare two groups, you can compare their RMSTs

the RMST via linear or log-linear models.

These models enable you to study the effects in the RMST

00:03:32,650 --> 00:03:36,810 Starting in SAS/STAT 15.1, new, dedicated features

You can use the RMST option in the LIFETEST procedure

to perform nonparametric analysis with respect

You can also use the new RMSTREG procedure

to fit linear and log-linear models of the RMST.

In PROC LIFETEST, you can perform RMST analysis

by specifying the RMST option in the PROC LIFETEST statement.

can specify the STRATA statement to compute the RMST

In addition to generating the survival plot,

you can also request the RMST curve by specifying the PLOTS=

You can use the MAXTIME= option to set the upper limit

You use the DIFF option in the STRATA statement

To protect yourself from falsely significant results,

you use the ADJ= option to make multiple-comparison adjustments

00:04:50,730 --> 00:04:53,470 Results from the RMST analyses are

displayed following the existing analyses in PROC LIFETEST.

By default, PROC LIFETEST uses the smallest value

among the largest observed times across the groups

As you can see from the “RMST Estimates” table,

the Large and Squamous groups appear to have larger RMST

estimates than the Adeno and Small groups.

You can interpret the RMST estimates as expected survival

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Performing Restricted Mean Survival Time Analysis (RMST) Using SAS/STAT

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significant

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