nri_cox
Net Reclassification Index for Cox Regression Models
nri_cox(data, formula0, formula1, t_risk, cutoff, B = FALSE, nboot = 10)
An object from which the following objects can be extracted:
data
dataset.
prob_orig
outcome risk probabilities at t_risk for reference model.
prob_new
outcome risk probabilities at t_risk for new model.
time
name of time variable.
status
name of status variable.
cutoff
cutoff value for survival probability.
t_risk
follow-up time used to calculate outcome (risk) probabilities.
reclass_totals
table with total reclassification numbers.
reclass_cases
table with reclassification numbers for cases.
reclass_controls
table with reclassification numbers for controls.
totals
totals of controls, cases, censored cases.
km_est
totals of cases calculated using Kaplan-Meiers risk estimates.
nri_est
reclassification measures.
Data frame with relevant predictors
A formula object to specify the reference model as normally used by glm. See under "Details" and "Examples" how these can be specified.
A formula object to specify the new model as normally used by glm.
Follow-up value to calculate cases, controls. See details.
A numerical vector that defines the outcome probability cutoff values.
A logical scalar. If TRUE bootstrap confidence intervals are calculated, if FALSE only the NRI estimates are reported.
A numerical scalar. Number of bootstrap samples to derive the percentile bootstrap confidence intervals. Default is 10.
Martijn Heymans, 2023
A typical formula object has the form Outcome ~ terms
. Categorical variables has to
be defined as Outcome ~ factor(variable)
, restricted cubic spline variables as
Outcome ~ rcs(variable, 3)
. Interaction terms can be defined as
Outcome ~ variable1*variable2
or Outcome ~ variable1 + variable2 + variable1:variable2
.
All variables in the terms part have to be separated by a "+". If a formula
object is used set predictors, cat.predictors, spline.predictors or int.predictors
at the default value of NULL.
Follow-up for which cases nd controls are determined. For censored cases before this follow-up
the expected risk of being a case is calculated by using the Kaplan-Meier value to calculate
the expected number of cases.These expected numbers are used to calculate the NRI proportions
but are not shown by function nricens
.
Cook NR, Ridker PM. Advances in measuring the effect of individual predictors of cardiovascular risk: the role of reclassification measures. Ann Intern Med. 2009;150(11):795-802.
Steyerberg EW, Pencina MJ. Reclassification calculations for persons with incomplete follow-up. Ann Intern Med. 2010;152(3):195-6; author reply 196-7.
Pencina MJ, D'Agostino RB Sr, Steyerberg EW. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med. 2011;30(1):11-21
Inoue E (2018). nricens: NRI for Risk Prediction Models with Time to Event and Binary Response Data. R package version 1.6, <https://CRAN.R-project.org/package=nricens>.
library(survival)
lbpmicox1 <- subset(psfmi::lbpmicox, Impnr==1) # extract one dataset
risk_est <- nri_cox(data=lbpmicox1, formula0 = Surv(Time, Status) ~ Duration + Pain,
formula1 = Surv(Time, Status) ~ Duration + Pain + Function + Radiation,
t_risk = 80, cutoff=c(0.45), B=TRUE, nboot=10)
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