240.ADVERSE EVENT SUMMARY TABLE WITH PERCENTAGE DISTRIBUTION ACROSS TREATMENT GROUPS USING DATA STEP IN SAS

ADVERSE EVENT SUMMARY TABLE WITH PERCENTAGE DISTRIBUTION ACROSS TREATMENT GROUPS USING DATA STEP IN SAS

options nocenter;

1.Mock Data

data ae;

  input STUDYID $ USUBJID $ TRT01P $ AEDECOD $ AESER $;

  datalines;

C001 001 Placebo Headache N

C001 002 DrugA Headache N

C001 003 DrugA Nausea N

C001 004 DrugB Headache Y

C001 005 Placebo Dizziness N

C001 006 DrugA Headache Y

C001 007 DrugB Nausea N

C001 008 Placebo Nausea N

C001 009 DrugB Dizziness Y

C001 010 DrugA Dizziness N

;

run;

proc print;run;

Output:

Obs	STUDYID	USUBJID	TRT01P	AEDECOD	AESER
1	C001	001	Placebo	Headache	N
2	C001	002	DrugA	Headache	N
3	C001	003	DrugA	Nausea	N
4	C001	004	DrugB	Headache	Y
5	C001	005	Placebo	Dizzines	N
6	C001	006	DrugA	Headache	Y
7	C001	007	DrugB	Nausea	N
8	C001	008	Placebo	Nausea	N
9	C001	009	DrugB	Dizzines	Y
10	C001	010	DrugA	Dizzines	N

2.Create Subject-Level Count by Treatment

proc sql;

  create table subj_n as

  select TRT01P, count(distinct USUBJID) as N

  from ae

  group by TRT01P;

quit;

proc print;run;

Output:

Obs	TRT01P	N
1	DrugA	4
2	DrugB	3
3	Placebo	3

3.Transpose AE Counts to Table Format

/* Step 1: Create ae_summary using PROC SQL */

proc sql;

  create table ae_summary as

  select AEDECOD, TRT01P,

         count(distinct USUBJID) as AE_Count

  from ae

  group by AEDECOD, TRT01P;

quit;

proc print;run;

Output:

Obs	AEDECOD	TRT01P	AE_Count
1	Dizzines	DrugA	1
2	Dizzines	DrugB	1
3	Dizzines	Placebo	1
4	Headache	DrugA	2
5	Headache	DrugB	1
6	Headache	Placebo	1
7	Nausea	DrugA	1
8	Nausea	DrugB	1
9	Nausea	Placebo	1

/* Step 2: Transpose the table to show treatment groups horizontally */

proc transpose data=ae_summary out=ae_trans prefix=Count_;

  by AEDECOD;

  id TRT01P;

  var AE_Count;

run;

proc print;run;

Output:

Obs	AEDECOD	_NAME_	Count_DrugA	Count_DrugB	Count_Placebo
1	Dizzines	AE_Count	1	1	1
2	Headache	AE_Count	2	1	1
3	Nausea	AE_Count	1	1	1

4.Merge with Subject Counts and Calculate Percentages

data final_table;

  set ae_trans;

  format Headline $200.;

  Headline = catx(' ',

                 AEDECOD,

                 put(Count_Placebo, 3.), '(', put(Count_Placebo/50*100, 4.1), '%)',

                 put(Count_DrugA, 3.),   '(', put(Count_DrugA/60*100, 4.1), '%)',

                 put(Count_DrugB, 3.),   '(', put(Count_DrugB/55*100, 4.1), '%)'

                 );

run;

proc print;run;

Output:

Obs	AEDECOD	_NAME_	Count_DrugA	Count_DrugB	Count_Placebo	Headline
1	Dizzines	AE_Count	1	1	1	Dizzines 1 ( 2.0 %) 1 ( 1.7 %) 1 ( 1.8 %)
2	Headache	AE_Count	2	1	1	Headache 1 ( 2.0 %) 2 ( 3.3 %) 1 ( 1.8 %)
3	Nausea	AE_Count	1	1	1	Nausea 1 ( 2.0 %) 1 ( 1.7 %) 1 ( 1.8 %)

5.Print the Final Table

proc print data=final_table noobs label;

  var Headline;

  label Headline = "Adverse Event Summary by Treatment (%)";

run;

Output:

Adverse Event Summary by Treatment (%)
Dizzines 1 ( 2.0 %) 1 ( 1.7 %) 1 ( 1.8 %)
Headache 1 ( 2.0 %) 2 ( 3.3 %) 1 ( 1.8 %)
Nausea 1 ( 2.0 %) 1 ( 1.7 %) 1 ( 1.8 %)

6.Listing Code

proc sort data=ae; by TRT01P AEDECOD USUBJID; run;

proc print;run;

Output:

Obs	STUDYID	USUBJID	TRT01P	AEDECOD	AESER
1	C001	010	DrugA	Dizzines	N
2	C001	002	DrugA	Headache	N
3	C001	006	DrugA	Headache	Y
4	C001	003	DrugA	Nausea	N
5	C001	009	DrugB	Dizzines	Y
6	C001	004	DrugB	Headache	Y
7	C001	007	DrugB	Nausea	N
8	C001	005	Placebo	Dizzines	N
9	C001	001	Placebo	Headache	N
10	C001	008	Placebo	Nausea	N

proc print data=ae label noobs;

  var USUBJID TRT01P AEDECOD AESER;

  label USUBJID="Subject ID"

        TRT01P="Treatment"

        AEDECOD="Adverse Event"

        AESER="Serious (Y/N)";

run;

Output:

Subject ID	Treatment	Adverse Event	Serious (Y/N)
010	DrugA	Dizzines	N
002	DrugA	Headache	N
006	DrugA	Headache	Y
003	DrugA	Nausea	N
009	DrugB	Dizzines	Y
004	DrugB	Headache	Y
007	DrugB	Nausea	N
005	Placebo	Dizzines	N
001	Placebo	Headache	N
008	Placebo	Nausea	N

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