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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