borrowing_hierarchical_commensurate: Hierarchical commensurate borrowing

In psborrow2: Bayesian Dynamic Borrowing Analysis and Simulation

Hierarchical commensurate borrowing

Description

Hierarchical commensurate borrowing

Usage

borrowing_hierarchical_commensurate(ext_flag_col, tau_prior)

Arguments

ext_flag_col	character. Name of the external flag column in the matrix.
tau_prior	Prior. Prior for the commensurability parameter.

Details

Method

In Bayesian dynamic borrowing using the hierarchical commensurate prior approach, external control information is borrowed to the extent that the outcomes (i.e., log hazard rates or log odds) are similar between external and internal control populations. See Viele 2014 \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/pst.1589")} and Hobbs 2011 \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/j.1541-0420.2011.01564.x")} for details.

External Control

The ext_flag_col argument refers to the column in the data matrix that contains the flag indicating a patient is from the external control cohort.

Tau Prior

The tau_prior argument specifies the hyperprior on the precision parameter commonly referred to as the commensurability parameter. See Viele 2014 \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/pst.1589")} for more details. This hyperprior determines (along with the comparability of the outcomes between internal and external controls) how much borrowing of the external control group will be performed. Example hyperpriors include largely uninformative inverse gamma distributions [e.g., prior_gamma(alpha = .001, beta = .001)] as well as more informative distributions [e.g., ⁠prior_gamma(alpha = 1, beta = .001⁠)], though any distribution x \in (0, \infty) can be used. Distributions with more density at higher values of x (i.e., higher precision) will lead to more borrowing.

Value

Object of class BorrowingHierarchicalCommensurate.

References

Viele, K., Berry, S., Neuenschwander, B., Amzal, B., Chen, F., Enas, N., Hobbs, B., Ibrahim, J.G., Kinnersley, N., Lindborg, S., Micallef, S., Roychoudhury, S. and Thompson, L. (2014), Use of historical control data for assessing treatment effects in clinical trials. Pharmaceut. Statist., 13: 41–54. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/pst.1589")}

Hobbes, B.P., Carlin, B.P., Mandrekar, S.J. and Sargent, D.J. (2011), Hierarchical commensurate and power prior models for adaptive incorporation of historical information in clinical trials. Biometrics, 67: 1047–1056. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/j.1541-0420.2011.01564.x")}

Examples

db <- borrowing_hierarchical_commensurate(
  ext_flag_col = "ext",
  tau_prior = prior_gamma(0.0001, 0.0001)
)

psborrow2 documentation built on April 4, 2025, 12:37 a.m.