Input commands are in blue.
Statements generated by PEANUTS are in green.
The data consists of individual records on breast cancer incidence and
radiation dose in a cohort of women who received repeated chest floroscopy
as part of their treatment for tuberculosis. These data consist of
a sample of 20 percent of the cohort members and all breast cancer cases,
whether or not they were included in the sample. This is a subset
of the data described by Z. Hrubec et al in Cancer Research, 49,
1989.
Describe and read the data. Since not all the variables are needed, a format statement is used.
NAMES id bcflag byr bmo bday bc icd8 xyr xmo xday
iyr imo iday dose agex @
FORMAT '(f4.0,f2.0,t12,f4.0,2f3.0,t23,f1.0,f4.0,t28,3f3.0,t37,3f3.0,t60,f8.3,t78,f5.2)'
@ ! Exclude
bilateral breast cancers
TRAN IF bc > 1 THEN DELETE ENDIF @
INPUT casechrt.dat @
Input from casechrt.dat
395
records read 395 records used
0 records rejected Workspace for 300 variables.
17 are currently defined. Up to 283 new
variables can be created
The MISS command indicates that values of dose
less than zero are to be treated as missing. Dose is rescaled and
a number of other transformations are made to compute age at exposure and
age at entry and other quantities.
MISS dose < 0 @
! Change to Gray
TRAN dose = dose/100 @
! Compute dates and ages
TRAN xyr = xyr + 1900;
iyr = iyr + 1900 ;
idate = julian(iyr,imo,iday)/365.25 ;
xdate = julian(xyr,xmo,xday)/365.25 ;
bdate = julian(byr,bmo,bday)/365.25 ;
xage = xdate - bdate ;
iage = idate - bdate ; @
Indicate the data are from a case-cohort study
with a 20 percent sampling fraction. and specify the case indicator (EVENT)
and the time variable. In this analysis the time scale for the background
hazard is attained age, but women do not enter the study until their first
treatment. Thus, iage is the entry-time variable.
CSCHT 0.2 @
EVENT bcflag @
ENTRY iage @
TIME xage @
Fit a linear dose response model with no effect
modifiers. This model can be written as:
LINE 1 dose @ FIT @
Sorting data on entry time ...
*** WARNING: Exit time exceeds entry time for
3 records
Subjects dropped from analysis
Iter Step Deviance
0 0 793.3531
1 0 782.7261
2 0 782.0896
3 0 782.0786
4 0 782.0786
Hazard function regression model
Case-cohort design with sampling fraction
0.200
Product additive excess RR model {RR = T0*(1
+ T1 + T2 + ...)}
XAGE is used for survival
time.
BCFLAG is used for outcomes
IAGE is used for entry
(left-truncation) times
Parameter Summary Table
# Name
Estimate Std.Err. Test Stat.
P value
-- ----------------------- ------------
---------- ----------- -------
Linear term 1
1 DOSE ....................
0.7731 0.3976
1.944 0.052
Records used =
390 Records dropped
= 5
Deviance =
782.079 Free parameters
= 1
Number of risk sets
= 75
Add age at exposure as an effect modifier.
The new model is :
LOGL 1 agex @
FIT @
Sorting data on entry time ...
Iter
Step Deviance
0 0 782.0786
1 0 781.2375
2 0 780.6490
3 0 780.5376
4 0 780.5328
5 0 780.5325
6 0 780.5325
Hazard function regression model
Case-cohort design with sampling fraction
0.200
Product additive excess RR model {RR = T0*(1
+ T1 + T2 + ...)}
XAGE is used for
survival time.
BCFLAG is used for outcomes
IAGE is used for
entry (left-truncation) times
Parameter Summary Table
# Name
Estimate Std.Err.
Test Stat. P value
-- ------------------- ------------
---------- ----------- -------
Linear term 1
1 DOSE ................
3.328 4.118
0.8083 0.419
Log-linear term 1
2 AGEX ................
-0.06408 0.05946 -1.078
0.281
Records used =
390 Records dropped
= 5
Deviance = 780.533
Free parameters
= 2
Number of risk sets =
75
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