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npi: Function to compute the Nottingham Prognostic Index

npi: Function to compute the Nottingham Prognostic Index
In genefu: Computation of Gene Expression-Based Signatures in Breast Cancer

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

This function computes the Nottingham Prognostic Index (NPI) as published in Galeat et al, 1992. NPI is a clinical index shown to be highly prognostic in breast cancer.

Usage

1
npi(size, grade, node, na.rm = FALSE)

Arguments

size

tumor size in cm.

grade

Histological grade, i.e. low (1), intermediate (2) and high (3) grade.

node

Nodal status. If only binary nodal status (0/1) is available, map 0 to 1 and 1 to 3.

na.rm

TRUE if missing values should be removed, FALSE otherwise.

Details

The risk prediction is either Good if score < 3.4, Intermediate if 3.4 <= score <- 5.4, or Poor if score > 5.4.

Value

score

Continuous signature scores

risk

Binary risk classification, 1 being high risk and 0 being low risk.

Author(s)

Benjamin Haibe-Kains

References

Galea MH, Blamey RW, Elston CE, and Ellis IO (1992) "The nottingham prognostic index in primary breast cancer", Breast Cancer Reasearch and Treatment, 22(3):207–219.

See Also

st.gallen

Examples

1
2
3
4
5
## load NKI dataset
data(nkis)
## compute NPI score and risk classification
npi(size=demo.nkis[ ,"size"], grade=demo.nkis[ ,"grade"],
  node=ifelse(demo.nkis[ ,"node"] == 0, 1, 3), na.rm=TRUE)

Example output

Loading required package: survcomp
Loading required package: survival
Loading required package: prodlim
Loading required package: mclust
Package 'mclust' version 5.3
Type 'citation("mclust")' for citing this R package in publications.
Loading required package: limma
Loading required package: biomaRt
Loading required package: iC10
Loading required package: pamr
Loading required package: cluster
Loading required package: iC10TrainingData
Loading required package: AIMS
Loading required package: e1071
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following object is masked from 'package:limma':

    plotMA

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colMeans, colSums, colnames, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, lengths, mapply, match, mget, order, paste, pmax, pmax.int,
    pmin, pmin.int, rank, rbind, rowMeans, rowSums, rownames, sapply,
    setdiff, sort, table, tapply, union, unique, unsplit, which,
    which.max, which.min

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

$score
  X.1   X.2   X.3   X.4   X.5   X.6   X.7   X.8   X.9  X.10  X.11  X.12  X.13 
 4.40  5.40  5.24  4.36  5.60  6.00  4.30  4.70  3.30  2.60  4.30  5.40  3.38 
 X.14  X.15  X.16  X.17  X.18  X.19  X.20  X.21  X.22  X.23  X.24  X.25  X.26 
 6.60  3.30  4.30  6.40  6.50  3.60  5.24  6.36  2.34  4.22  4.40  3.24  2.30 
 X.27  X.28  X.29  X.30  X.31  X.32  X.33  X.34  X.35  X.36  X.37  X.38  X.39 
 4.42  3.60  4.28  6.56  3.60  4.30  5.56  5.30  4.52  2.36  4.14  3.50  6.60 
 X.40  X.41  X.42  X.43  X.44  X.45  X.46  X.47  X.48  X.49  X.50  X.51  X.52 
 3.40  2.14  4.60  4.36  3.34  2.40  2.20  2.20  4.64  5.70  6.48  3.34  4.30 
 X.53  X.54  X.55  X.56  X.57  X.58  X.59  X.60  X.61  X.62  X.63  X.64  X.65 
 4.50  5.60  4.20  5.36  5.42  4.42  4.54  5.48  5.30  4.54  4.36  3.54  5.26 
 X.66  X.67  X.68  X.69  X.70  X.71  X.72  X.73  X.74  X.75  X.76  X.77  X.78 
 6.50  4.28  6.36  3.30  6.40  4.30  6.30  4.36  5.50  2.32  6.60  4.50  3.24 
 X.79  X.80  X.81  X.82  X.83  X.84  X.85  X.86  X.87  X.88  X.89  X.90  X.91 
 4.50  4.52  5.70  6.40  3.28  3.26  5.40  4.60  4.80  6.70  4.50  5.50  5.40 
 X.92  X.93  X.94  X.95  X.96  X.97  X.98  X.99 X.100 X.101 X.102 X.103 X.104 
 5.44  4.40  4.36  3.38  4.54  4.36  4.30  4.40  4.50  2.26  4.50  4.60  4.40 
X.105 X.106 X.107 X.108 X.109 X.110 X.111 X.112 X.113 X.114 X.115 X.116 X.117 
 6.60  4.50  4.60  3.40  2.26  5.44  5.40  5.40  6.80  3.28  2.20  4.80  5.84 
X.118 X.119 X.120 X.121 X.122 X.123 X.124 X.125 X.126 X.127 X.128 X.129 X.130 
 4.40  4.60  4.40  3.20  4.40  3.54  6.36  4.44  4.60  6.20  4.60  4.30  4.24 
X.131 X.132 X.133 X.134 X.135 X.136 X.137 X.138 X.139 X.140 X.141 X.142 X.143 
 5.40  6.36  6.50  6.44  3.70  4.56  4.40  5.50  4.70  3.34  6.50  5.80  3.40 
X.144 X.145 X.146 X.147 X.148 X.149 X.150 
 6.00  3.60  2.34  4.36  3.50  4.70  3.50 

$risk
           X.1            X.2            X.3            X.4            X.5 
"Intermediate" "Intermediate" "Intermediate" "Intermediate"         "Poor" 
           X.6            X.7            X.8            X.9           X.10 
        "Poor" "Intermediate" "Intermediate"         "Good"         "Good" 
          X.11           X.12           X.13           X.14           X.15 
"Intermediate" "Intermediate"         "Good"         "Poor"         "Good" 
          X.16           X.17           X.18           X.19           X.20 
"Intermediate"         "Poor"         "Poor" "Intermediate" "Intermediate" 
          X.21           X.22           X.23           X.24           X.25 
        "Poor"         "Good" "Intermediate" "Intermediate"         "Good" 
          X.26           X.27           X.28           X.29           X.30 
        "Good" "Intermediate" "Intermediate" "Intermediate"         "Poor" 
          X.31           X.32           X.33           X.34           X.35 
"Intermediate" "Intermediate"         "Poor" "Intermediate" "Intermediate" 
          X.36           X.37           X.38           X.39           X.40 
        "Good" "Intermediate" "Intermediate"         "Poor" "Intermediate" 
          X.41           X.42           X.43           X.44           X.45 
        "Good" "Intermediate" "Intermediate"         "Good"         "Good" 
          X.46           X.47           X.48           X.49           X.50 
        "Good"         "Good" "Intermediate"         "Poor"         "Poor" 
          X.51           X.52           X.53           X.54           X.55 
        "Good" "Intermediate" "Intermediate"         "Poor" "Intermediate" 
          X.56           X.57           X.58           X.59           X.60 
"Intermediate"         "Poor" "Intermediate" "Intermediate"         "Poor" 
          X.61           X.62           X.63           X.64           X.65 
"Intermediate" "Intermediate" "Intermediate" "Intermediate" "Intermediate" 
          X.66           X.67           X.68           X.69           X.70 
        "Poor" "Intermediate"         "Poor"         "Good"         "Poor" 
          X.71           X.72           X.73           X.74           X.75 
"Intermediate"         "Poor" "Intermediate"         "Poor"         "Good" 
          X.76           X.77           X.78           X.79           X.80 
        "Poor" "Intermediate"         "Good" "Intermediate" "Intermediate" 
          X.81           X.82           X.83           X.84           X.85 
        "Poor"         "Poor"         "Good"         "Good" "Intermediate" 
          X.86           X.87           X.88           X.89           X.90 
"Intermediate" "Intermediate"         "Poor" "Intermediate"         "Poor" 
          X.91           X.92           X.93           X.94           X.95 
"Intermediate"         "Poor" "Intermediate" "Intermediate"         "Good" 
          X.96           X.97           X.98           X.99          X.100 
"Intermediate" "Intermediate" "Intermediate" "Intermediate" "Intermediate" 
         X.101          X.102          X.103          X.104          X.105 
        "Good" "Intermediate" "Intermediate" "Intermediate"         "Poor" 
         X.106          X.107          X.108          X.109          X.110 
"Intermediate" "Intermediate" "Intermediate"         "Good"         "Poor" 
         X.111          X.112          X.113          X.114          X.115 
"Intermediate" "Intermediate"         "Poor"         "Good"         "Good" 
         X.116          X.117          X.118          X.119          X.120 
"Intermediate"         "Poor" "Intermediate" "Intermediate" "Intermediate" 
         X.121          X.122          X.123          X.124          X.125 
        "Good" "Intermediate" "Intermediate"         "Poor" "Intermediate" 
         X.126          X.127          X.128          X.129          X.130 
"Intermediate"         "Poor" "Intermediate" "Intermediate" "Intermediate" 
         X.131          X.132          X.133          X.134          X.135 
"Intermediate"         "Poor"         "Poor"         "Poor" "Intermediate" 
         X.136          X.137          X.138          X.139          X.140 
"Intermediate" "Intermediate"         "Poor" "Intermediate"         "Good" 
         X.141          X.142          X.143          X.144          X.145 
        "Poor"         "Poor" "Intermediate"         "Poor" "Intermediate" 
         X.146          X.147          X.148          X.149          X.150 
        "Good" "Intermediate" "Intermediate" "Intermediate" "Intermediate"

genefu documentation built on Jan. 28, 2021, 2:01 a.m.

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