Add_CostBenefit_Axis

xlim

Character vector of the form c('c1:b1', 'c2:b2', ..., 'cn:bn') with integers ci, bi corresponding to specific cost:benefit ratios to print.

cost.benefits

number of cost:benefit ratios to print if cost.benefit.axis = TRUE (default n.cost.benefit = 6).

n.cost.benefits

x-axis line to print the axis (default is 4).

line

Either 'opt-in' (default) or 'opt-out', describing the type of policy for which to report the net benefit. A policy is 'opt-in' when the standard-of-care for a population is to assign a particular 'treatment' to no one. Clinicians then use a risk model to categorize patients as 'high-risk', with the recommendation to treat high-risk patients with some intervention. Alternatively, an 'opt-out' policy is applicable to contexts where the standard-of-care is to recommend a treatment to an entire patient population. The potential use of a risk model in this setting is to identify patients who are 'low-risk' and recommend that those patients 'opt-out' of treatment.

policy

Add cost benefit ratio axis to a decision curve plot.

Decision curves are a useful tool to evaluate the population impact
of adopting a risk prediction instrument into clinical practice. Given one or more
instruments (risk models) that predict the probability of a binary outcome, this
package calculates and plots decision curves, which display estimates of the
standardized net benefit by the probability threshold used to categorize observations
as 'high risk.' Curves can be estimated using data from an observational cohort, or
from case-control studies when an estimate of the population outcome prevalence
is available. Confidence intervals calculated using the bootstrap can be displayed and
a wrapper function to calculate cross-validated curves using k-fold cross-validation is
also provided.

Add_CostBenefit_Axis: Add cost benefit ratio axis to a decision curve plot.

Description

Usage

Arguments

Value

See Also