Survival Analysis - SAS

A SIMULATION STUDY OF ESTIMATORS IN STRATIFIED PROPORTIONAL HAZARDS MODELS

RISK EVALUATION AFTER HEART VALVE REPLACEMENT BY SAS PROC PHREG

Everything to know about Clinical Trails

Clinical Trails 

A clinical trial (also clinical research) is a research study in human volunteers to answer specific health questions. Carefully conducted clinical trials are the fastest and safest ways to find treatments that work in people and ways to improve health. Interventional trials determine whether experimental treatments or new ways of using known therapies are safe and effective under controlled environments. Observational trials address health issues in large groups of people of populations in natural settings.

Protocol

All clinical trials must be conducted according to strict scientific and ethical principles. Every clinical trial must have a protocol, or action plan that describes what will be done in the study, how it will be conducted, and why each part of the study is necessary - including details such as the criteria for patient participation, the schedule of tests, procedures, and medications, and the length of the study.

Phases of Clinical Trials

Clinical trials are conducted in a series of steps, called phases - each phase is designed to answer a separate research question.
Phase I: Researchers test a new drug or treatment in a small group of people for the first time to evaluate its safety, determine a safe dosage range, and identify side effects.
Phase II: The drug or treatment is given to a larger group of people to see if it is effective and to further evaluate its safety.
Phase III: The drug or treatment is given to large groups of people to confirm its effectiveness, monitor side effects, compare it to commonly used treatments, and collect information that will allow the drug or treatment to be used safely.
Phase IV: Studies are done after the drug or treatment has been marketed to gather information on the drug's effect in various populations and any side effects associated with long-term use.

Below are the links to papers published in various SAS User Group Meetings which are very informative to any SAS programmer: novice or seasoned


Clinical Trails Basics

SAS Programmer to Clinical SAS Programmer

Clinical Programming for Novice

Clinical Trials terminology for SAS Programmers

Managing Clinical Trials Data using SAS Software 

Clinical Trial Terminology

Clinical Study Design and Methods Terminology

Clinical Trial Terms

Annotate CRF
 
Annotate Case  Report Form Automation System

A Regular Language: The Annotated Case Report Form


Table, Listing and Graphs

Pharmaceutical Programming: From CRFs to Tables, Listings and Graphs, a process overview with real world examples

Creating Tables or Listings with a Zero-Record SAS® Data Set -- Basic Program Structure and Three Simple Techniques

Clinical Trial Reporting Using SAS/GRAPH SG Procedures

Show Your Graphs and Tables at Their Best on the Web with ODS 

Creating Clinical Trial Summary Tables Containing P-Values:A Practical Approach Using Standard SAS Macros

Clinical Trials Validation 

The 5 Most Important Clinical SAS Programming Validation Steps

A Simple Solution for Managing the Validation of SAS Programs That Support Regulatory Submissions   


Clinical Trials Submissions

Data Definition Tables – Definition and Automation


Acknowledgements:
U.S National Library of Medicine

Descriptive Statistics in SAS (Part -1) - PROC MEANS and PROC SUMMARY

Data Source: 2015 Google Data for Unemployment

The most commonly used SAS Statistical procedures are Means, Summary, Frequency and Univariate we will take a detailed look at each of them.

Part 1- PROC MEANS

Syntax:
 PROC MEANS <DATA=SAS-data-set>
    <statistic-keyword(s)><option(s)>;
Run:

 
where

• SAS-data-set is the name of the data set to be used
• statistic-keyword(s) specify the statistics to compute
• option(s) control the content, analysis, and appearance of output

 PROC MEANS prints the n-count (number of non missing values), the mean, the standard deviation, and the minimum and maximum values of every numeric variable in a data set. You may not always want this default statistics produced by PROC MEANS, so you can specific other statistic-keywords. Statistic-keywords that can be used with PROC MEANS are:

Descriptive Statistics

Keyword	Description
CLM	Two-sided confidence limit for the mean
CSS	Corrected sum of squares
CV	Coefficient of variation
KURTOSIS	Kurtosis
LCLM	One-sided confidence limit below the mean
MAX	Maximum value
MEAN	Average
MIN	Minimum value
N	Number of observations with nonmissing values
NMISS	Number of observations with missing values
RANGE	Range
SKEWNESS	Skewness
STDDEV / STD	Standard deviation
STDERR	Standard error of the mean
SUM	Sum
SUMWGT	Sum of the Weight variable values.
UCLM	One-sided confidence limit above the mean
USS	Uncorrected sum of squares
VAR	Variance

Quantile Statistics

Keyword	Description
MEDIAN / P50	Median or 50th percentile
P1	1st percentile
P5	5th percentile
P10	10th percentile
Q1 / P25	Lower quartile or 25th percentile
Q3 / P75	Upper quartile or 75th percentile
P90	90th percentile
P95	95th percentile
P99	99th percentile
QRANGE	Difference between upper and lower quartiles: Q3-Q1

Hypothesis Testing

Keyword	Description
PROBT	Probability of a greater absolute value for the t value
T	Student's t for testing the hypothesis that the population mean is 0

Let us see an example:

Write a program to import excel file, know the content of dataset and produce the mean of numeric variables in the data set work.unemployment

  The unemployment dataset contains 62000 observations but we calculated the means of first 10 observation by using obs option. As can be seen, by use of PROC CONTENTS statement we get to know the type of variable (char/num), a simple Means Procedure will produce n-count (number of nonmissing values), the mean, the standard deviation and the minimum and maximum values of  all the 8 numeric variable  present in the data set

 

 

 

Write a Proc Means using other descriptive statistics like max and maxdec.  Use var statement to limit the number of variables and also use class statement to group the observation.

We will now select only  max value of variables January_Employment, February_Employment, March_Employment and Total_Quarterly_Wages. Maxdecimal specifies the maximum number of decimal places in result. To produce separate analyses of grouped observations, add a CLASS statement to the MEANS procedure. PROC MEANS does not generate statistics for CLASS variables, because their values are used only to categorize data. CLASS variables can be either character or numeric. A BY statement can also be used but unlike CLASS Statement By statement requires data to be in sorted order or indexed in order. Also it will produce different

A BY statement can also be used but unlike CLASS Statement By statement requires data to be in sorted order or indexed in order. Also it will produce different output than class. As can be seen below BY statement produces separate table for each BY variable.

 

 

 

 

A summarized output data set can be created by using PROC SUMMARY. When you use PROC SUMMARY, you use the same code to produce the output data set that you would use with PROC MEANS.
The difference between the two procedures is that PROC MEANS produces a report by default (remember that you can use the NOPRINT option to suppress the default report). By contrast, to produce a report in PROC SUMMARY, you must include a PRINT option in the PROC SUMMARY statement.

 

 

 

 

 

 

 

 

String extraction using SAS Scan and Substr functions

In my last blog we saw string extraction using perl function. Today we are going to extract and concatenate character string using SAS Scan and Substr functions. Syntax:      SCAN(argument,n,<delimiters>) where argument specifies the character variable or expression to scan. n specifies which word to read. delimiters are special characters that must be enclosed in single quotation marks (' '). If you do not specify delimiters, default delimiters are used.       SUBSTR(argument,position,<n>)  where argument specifies the character variable or expression to scan. position is the character position to start from. n specifies the number of characters to extract. If n is omitted, all remaining characters are included in the substring.  Let us see an example: In the dataset work.Company there are four columns Name, Age, Sex and SSN. We wants to create a new data set employeeID with a column named ID which contains unique Identification number for the employees based on their last name and last four digits of their  SSN. Company g Obs Name Age Sex SSN 1 Morrison, Michael 32 M 2 Rudelich, Herbert 39 M 129-42-9261 3 Vincent, Martina 34 F 074-53-9892 4 Benito, Gisela 32 F 228-88-9649 5 Sirignano, Emily 12 F 442-21-8075 6 Harbinger, Nicholas 36 M 446-93-2122 7 Phillipon, Marie-Odile 28 F 776-84-5391 8 Gunter, Thomas 27 M 929-75-0218       data employeeID;  set company;  ID = (scan(name, 1, ","))!!(substr(SSN,8,4));  run;  proc print data=employeeID;  run; Explanation: scan(name, 1, ",") name is the character variable to scan 1 is the position of the word to read "," is the delimiter substr(SSN,8,4) SSN is the character variable to scan. 8 is the character position to start from. 4 specifies the number of characters to extract Result Obs Name Age Sex SSN ID 1 Morrison, Michael 32 M Morrison 2 Rudelich, Herbert 39 M 129-42-9261 Rudelich9261 3 Vincent, Martina 34 F 074-53-9892 Vincent9892 4 Benito, Gisela 32 F 228-88-9649 Benito9649 5 Sirignano, Emily 12 F 442-21-8075 Sirignano8075 6 Harbinger, Nicholas 36 M 446-93-2122 Harbinger2122 7 Phillipon, Marie-Odile 28 F 776-84-5391 Phillipon5391 8 Gunter, Thomas 27 M 929-75-0218 Gunter0218

String Extraction Using Perl Regular Expressions (PRX) in SAS

The PRXMATCH function searches source with the perl-regular-expression and returns the position at which the string begins.  If there is no match, PRXMATCH returns a zero.

syntax : PRXMATCH (perl-regular-expression, source)

Suppose we have a list of companies and their addresses :

7‑Eleven, Inc.community relations department dallas, TX 75221-0711

20 Century Fox 10201 pico blvd, los angeles, CA 90064

APACHE prime four business park kingswells scotland, United Kingdom

We wish to extract the names of the companies. The names of the companies starts with either a upper-case letters or numbers while their  addresses are in the lower-case. To do so we are going to the string extraction with the help of PRXMATCH Function.

Explanaton:

prxmatch ('/\b[a-z]\w*\b/')

In this example we are using forward slashes (/) as perl dilimiters.

 \b is word boundary (a space or end-of-line)

[a-z] matches lower-case letters

\w matches any word character (upper- and lowercase letters, blank and underscore)

* matches the previous subexpression zero or more times

As can be seen in the result  PRXMATCH function  helped us to extract the names of the companies.