cox.wpc.est: Generate Weighted Predictiveness Curve Estimates Using...

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

View source: R/cox.wpc.est.R

Description

This function generates weighted predictiveness curve estimates and/or confident bands using parametric approach.

Usage

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cox.wpc.est(event, censor, marker, cutoff, quantile)

Arguments

event

This is the survival time. It is a positive numerical vector with no missing values.

censor

This specifies censor information. It is a vector, with 1 indicating an event and 0 indicating right censored. No missing values are allowed.

marker

This is the biomarker information (or other interesting variables). It is numerical with no missing values.

cutoff

This is to define the time cutoff.

quantile

This specifies the quantile of the confident band. Default is 0.95, 95% Confident band will be generated.

Details

The Cox proportional hazard model with a single biomarker will be used to derive and draw the predictiveness curve for parametric WPC. The relationship could be written in the form of the survival function as follows: S(t)=[S_0(t)]^{exp{xβ}}, where S(t) is survival function, S_0(t) is baseline survivor function, and x is the biomarker of interest. The effect of the biomarker is expressed by the exp(xβ) term and quantified as a shift from the baseline survival S_0(t). Because S_0(t) is always between 0 and 1, a positive coefficient β will decrease the survival function with increasing biomarker values; a negative coefficient β will increase the survival function with decreasing biomarker values. For any given time t, the baseline survival function S_0(t) could be estimated. Therefore, with a fixed coefficient estimate and fixed time, we could do such prediction for a range of x values by fitting x values into the formula earlier and then connect the predictions derived from the smallest x value to the largest x value. That will form the predictiveness curve for that particular time point.

Value

A list with components:

x

a vector of biomarker values.

s

A vector of survival rate estimates for each biomarker value.

lb

A vector of confident lower bands

ub

A vector of confident upper band

Author(s)

Hui Yang huiy@amgen.com, Rui Tang rui_tang@vrtx.com and Jing Huang jinghuang0@gmail.com

References

Yang H., Tang R., Hale M. and Huang J. (2016) A visualization method measuring the performance of biomarkers for guiding treatment decisions Pharmaceutical Statistics, 15(2), 1539-1612

See Also

npr.wpc.est

Examples

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	## install packages "survival" and "msm"
	
	library("survival")
	library("msm")

	cox.object = cox.wpc.est(event=wpcdata$OSday, censor=wpcdata$OScensor, 
	marker=wpcdata$Biomarker1,cutoff=180,quantile=0.95)
	
	print(cox.object)

WPC documentation built on May 2, 2019, 6:52 a.m.