1. Introduction
remss from github is a package for TNM
stage is important in treatment decision-making and outcome predicting.
The existing oropharyngeal Cancer (OPC) TNM stages have not made
distinction of the two sub sites of HPV+ and HPV- diseases.We developed
novel criteria to assess performance of the TNM stage grouping schemes
based on parametric modeling adjusting on important clinical factors.
These criteria evaluate the TNM stage grouping scheme in five different
measures: hazard consistency, hazard discrimination, explained
variation, likelihood difference, and balance.
Reference:
“Xu, W., et al. ’Refining evaluation methodology on TNM stage system:
assessment on HPV-related oropharyngeal cancer.’Austin Biometrics and
Biostatistics 2 (2015): 1014.” (via)
2. Installation
You can install remss from [github] (https://github.com/qiuanzhu/remss):
library("devtools")
install_github("qiuanzhu/remss")
#3. Examples
In the following examples, a simulated dataset with 10 variables and
504 observations.
library("remss")
head(Rdata)
#>
#> Attaching package: 'remss'
#> The following object is masked from 'package:base':
#>
#> rank
1 |
0 |
64.0 |
1 |
101.55616 |
Treatment 1 |
G13 |
II |
II |
III |
2 |
0 |
60.2 |
1 |
37.64384 |
Treatment 2 |
G2 |
I |
II |
II |
3 |
1 |
64.7 |
0 |
73.15068 |
Treatment 1 |
G17 |
II |
III |
IV |
4 |
1 |
64.6 |
0 |
127.56164 |
Treatment 1 |
G12 |
II |
II |
III |
5 |
0 |
53.2 |
0 |
49.24932 |
Treatment 1 |
G2 |
I |
II |
II |
6 |
1 |
51.5 |
0 |
83.80274 |
Treatment 1 |
G17 |
II |
III |
IV |
There are three grouping schemes
(Scheme.1,Scheme.2,Scheme.3)
base on the classification (Basic_group). Five measures
of grouping scheme and weight for each measurement are introduced.
data(Rdata)
Scheme=c('Scheme.1','Scheme.2','Scheme.3')
Covar=c('Age','Treatment')
weight=c(1,1,0.5,0.5,1)
Order=list(c('I','II','III'),c('I','II','III','IV'),c('I','II','III','IV'))
table<-rank(os='OS',ostime='survmonth',groupvar='Basic_group', scheme=Scheme, order=Order, covariate=Covar,weight=weight,data=Rdata)
#> Warning in coxph.fit(X, Y, istrat, offset, init, control, weights = weights, :
#> Loglik converged before variable 16,19 ; coefficient may be infinite.
Variable Information:
OS |
1 |
0.2639 |
0.4412 |
Null |
survmonth |
1 |
72.1517 |
39.657 |
Null |
Basic_group |
0 |
NA |
NA |
G1 , G10, … |
Scheme.1 |
0 |
NA |
NA |
I , II , … |
Scheme.2 |
0 |
NA |
NA |
I , II , … |
Scheme.3 |
0 |
NA |
NA |
I , II , … |
Age |
1 |
51.6038 |
12.8468 |
Null |
Treatment |
0 |
NA |
NA |
Treatment 1, Treatment 2 |
|
Observation number:
Hazard Consistency Measurement:
2 |
Scheme.2 |
1.659162 |
0.0000000 |
1 |
1 |
Scheme.1 |
2.042695 |
0.8535856 |
2 |
3 |
Scheme.3 |
2.108482 |
1.0000000 |
3 |
|
Hazard Discrimination Measurement:
Scheme.1 |
0.0969022 |
0.0000000 |
1 |
Scheme.2 |
0.3479726 |
0.0928677 |
2 |
Scheme.3 |
2.8004306 |
1.0000000 |
3 |
|
Likelihood Difference Measurement:
Scheme.1 |
20.93218 |
0.0000000 |
1 |
Scheme.2 |
16.68120 |
0.6394996 |
2 |
Scheme.3 |
14.28482 |
1.0000000 |
3 |
|
Explained Variance Measurement:
2 |
Scheme.2 |
21.44556 |
0.0000000 |
1 |
1 |
Scheme.1 |
19.90845 |
0.6062326 |
2 |
3 |
Scheme.3 |
18.91005 |
1.0000000 |
3 |
|
Balance Measurement:
1 |
Scheme.1 |
0.4126984 |
0.0000000 |
1 |
3 |
Scheme.3 |
0.5039683 |
0.6969697 |
2 |
2 |
Scheme.2 |
0.5436508 |
1.0000000 |
3 |
|
Overall Rank:
Scheme.1 |
1.156702 |
1 |
Scheme.2 |
1.412618 |
2 |
Scheme.3 |
3.696970 |
3 |
|