nri_cox: Net Reclassification Index for Cox Regression Models

In psfmi: Prediction Model Pooling, Selection and Performance Evaluation Across Multiply Imputed Datasets

Net Reclassification Index for Cox Regression Models

Description

nri_cox Net Reclassification Index for Cox Regression Models

Usage

nri_cox(data, formula0, formula1, t_risk, cutoff, B = FALSE, nboot = 10)

Arguments

data	Data frame with relevant predictors
formula0	A formula object to specify the reference model as normally used by glm. See under "Details" and "Examples" how these can be specified.
formula1	A formula object to specify the new model as normally used by glm.
t_risk	Follow-up value to calculate cases, controls. See details.
cutoff	A numerical vector that defines the outcome probability cutoff values.
B	A logical scalar. If TRUE bootstrap confidence intervals are calculated, if FALSE only the NRI estimates are reported.
nboot	A numerical scalar. Number of bootstrap samples to derive the percentile bootstrap confidence intervals. Default is 10.

Details

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.

Value

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.

Author(s)

Martijn Heymans, 2023

References

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>.

Examples

  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)

psfmi documentation built on July 9, 2023, 7:02 p.m.