Hello everyone,
I am new to this forum. I am a stata user but I don't have much background in statistics. I did CoxPH model to detect association between risk of hypertrophic cardiomyopathy (phenopos_fup) in different genotype groups(genotype_group) adjusted for age at 1st echocardiogram (age_1st echo) and sex. I check PH assumption after the test and found that age_1stecho violated the assumption. So, I re-ran the model by adding age_1stecho as tvc. But it didn't seem to fix the violation. In this case, how could I proceed? My main interest is risk of HCM in different genotype. Can I still interpret the effect size as it is in model 1 and ignore the PH assumption violation for age as it's not main effect I am interested in?
Model 1
. stcox i.sex age_1stecho i.genotype_group,nolog
Failure _d: phenopos_fup==1
Analysis time _t: time_to_phenopos
Cox regression with no ties
No. of subjects = 581 Number of obs = 581
No. of failures = 105
Time at risk = 7,065.6012
LR chi2(4) = 77.15
Log likelihood = -524.05486 Prob > chi2 = 0.0000
-----------------------------------------------------------------------------------
_t | Haz. ratio Std. err. z P>|z| [95% conf. interval]
------------------+----------------------------------------------------------------
sex |
Female | .6368161 .1330752 -2.16 0.031 .4228037 .959156
age_1stecho | .8817264 .0198928 -5.58 0.000 .8435867 .9215904
|
genotype_group |
Genotype - | .8720211 .2339626 -0.51 0.610 .5154069 1.475379
Genotype unknown | .2573629 .0581113 -6.01 0.000 .1653289 .4006295
-----------------------------------------------------------------------------------
. estat phtest,detail
Test of proportional-hazards assumption
Time function: Analysis time
--------------------------------------------------------
| rho chi2 df Prob>chi2
-------------+------------------------------------------
1b.sex | . . 1 .
2.sex | -0.14604 2.34 1 0.1260
age_1stecho | 0.51468 16.61 1 0.0000
1b.genotyp~p | . . 1 .
2.genotype~p | 0.04664 0.22 1 0.6358
3.genotype~p | 0.08506 0.76 1 0.3819
-------------+------------------------------------------
Global test | 18.81 4 0.0009
--------------------------------------------------------
Model 2
. stcox i.sex age_1stecho i.genotype_group,tvc(age_1stecho) nolog
Failure _d: phenopos_fup==1
Analysis time _t: time_to_phenopos
Cox regression with no ties
No. of subjects = 581 Number of obs = 581
No. of failures = 105
Time at risk = 7,065.6012
LR chi2(5) = 98.98
Log likelihood = -513.13588 Prob > chi2 = 0.0000
-----------------------------------------------------------------------------------
_t | Haz. ratio Std. err. z P>|z| [95% conf. interval]
------------------+----------------------------------------------------------------
main |
sex |
Female | .62324 .1298635 -2.27 0.023 .414278 .9376026
age_1stecho | .6223885 .0538531 -5.48 0.000 .5253032 .7374169
|
genotype_group |
Genotype - | .8949743 .2401153 -0.41 0.679 .52898 1.514195
Genotype unknown | .2524777 .0571142 -6.08 0.000 .1620573 .3933485
------------------+----------------------------------------------------------------
tvc |
age_1stecho | 1.028269 .0067182 4.27 0.000 1.015185 1.041521
-----------------------------------------------------------------------------------
Note: Variables in tvc equation interacted with _t.
Thanks
Sandar
.
I am new to this forum. I am a stata user but I don't have much background in statistics. I did CoxPH model to detect association between risk of hypertrophic cardiomyopathy (phenopos_fup) in different genotype groups(genotype_group) adjusted for age at 1st echocardiogram (age_1st echo) and sex. I check PH assumption after the test and found that age_1stecho violated the assumption. So, I re-ran the model by adding age_1stecho as tvc. But it didn't seem to fix the violation. In this case, how could I proceed? My main interest is risk of HCM in different genotype. Can I still interpret the effect size as it is in model 1 and ignore the PH assumption violation for age as it's not main effect I am interested in?
Model 1
. stcox i.sex age_1stecho i.genotype_group,nolog
Failure _d: phenopos_fup==1
Analysis time _t: time_to_phenopos
Cox regression with no ties
No. of subjects = 581 Number of obs = 581
No. of failures = 105
Time at risk = 7,065.6012
LR chi2(4) = 77.15
Log likelihood = -524.05486 Prob > chi2 = 0.0000
-----------------------------------------------------------------------------------
_t | Haz. ratio Std. err. z P>|z| [95% conf. interval]
------------------+----------------------------------------------------------------
sex |
Female | .6368161 .1330752 -2.16 0.031 .4228037 .959156
age_1stecho | .8817264 .0198928 -5.58 0.000 .8435867 .9215904
|
genotype_group |
Genotype - | .8720211 .2339626 -0.51 0.610 .5154069 1.475379
Genotype unknown | .2573629 .0581113 -6.01 0.000 .1653289 .4006295
-----------------------------------------------------------------------------------
. estat phtest,detail
Test of proportional-hazards assumption
Time function: Analysis time
--------------------------------------------------------
| rho chi2 df Prob>chi2
-------------+------------------------------------------
1b.sex | . . 1 .
2.sex | -0.14604 2.34 1 0.1260
age_1stecho | 0.51468 16.61 1 0.0000
1b.genotyp~p | . . 1 .
2.genotype~p | 0.04664 0.22 1 0.6358
3.genotype~p | 0.08506 0.76 1 0.3819
-------------+------------------------------------------
Global test | 18.81 4 0.0009
--------------------------------------------------------
Model 2
. stcox i.sex age_1stecho i.genotype_group,tvc(age_1stecho) nolog
Failure _d: phenopos_fup==1
Analysis time _t: time_to_phenopos
Cox regression with no ties
No. of subjects = 581 Number of obs = 581
No. of failures = 105
Time at risk = 7,065.6012
LR chi2(5) = 98.98
Log likelihood = -513.13588 Prob > chi2 = 0.0000
-----------------------------------------------------------------------------------
_t | Haz. ratio Std. err. z P>|z| [95% conf. interval]
------------------+----------------------------------------------------------------
main |
sex |
Female | .62324 .1298635 -2.27 0.023 .414278 .9376026
age_1stecho | .6223885 .0538531 -5.48 0.000 .5253032 .7374169
|
genotype_group |
Genotype - | .8949743 .2401153 -0.41 0.679 .52898 1.514195
Genotype unknown | .2524777 .0571142 -6.08 0.000 .1620573 .3933485
------------------+----------------------------------------------------------------
tvc |
age_1stecho | 1.028269 .0067182 4.27 0.000 1.015185 1.041521
-----------------------------------------------------------------------------------
Note: Variables in tvc equation interacted with _t.
Thanks
Sandar
.
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