MetaAnalyticSurvCont {Surrogate}R Documentation

Compute surrogacy measures for a continuous (normally-distributed) surrogate and a time-to-event true endpoint in the meta-analytic multiple-trial setting.

Description

The function 'MetaAnalyticSurvCont()' fits the model for a continuous surrogate and time-to-event true endpoint described by Alonso et al. (2016) in the meta-analytic multiple-trial setting.

Usage

MetaAnalyticSurvCont(
  data,
  true,
  trueind,
  surrog,
  trt,
  center,
  trial,
  patientid,
  copula,
  adjustment
)

Arguments

data

A data frame with the correct columns (See Data Format).

true

Observed time-to-event for true endpoint.

trueind

Time-to-event indicator for the true endpoint.

surrog

Continuous surrogate endpoint.

trt

Treatment indicator.

center

Center indicator (equal to trial if there are no different centers). This is the unit for which specific treatment effects are estimated.

trial

Trial indicator. This is the unit for which common baselines are to be used.

patientid

Patient indicator.

copula

The copula that is used, either "Clayton", "Hougaard" or "Plackett"

adjustment

The adjustment that should be made for the trial-level surrogacy, either "unadjusted", "weighted" or "adjusted"

Value

Returns an object of class "MetaAnalyticSurvCont" that can be used to evaluate surrogacy and contains the following elements:

Model

In the model, a copula-based model is used for the true time-to-event endpoint and the surrogate continuous, normally distributed endpoint. More specifically, three copulas can be used: the Clayton copula, Hougaard copula and Plackett copula. The marginal model for the true endpoint is the proportional hazard model. The marginal model for the surrogate endpoint is the classical linear regression model. The quality of the surrogate at the individual level can be evaluated by either Kendall's \tau or Spearman's \rho, depending on which copula function is used. The quality of the surrogate at the trial level can be evaluated by considering the R^2_{trial} between the estimated treatment effects.

Data Format

The data frame must contains the following columns:

Author(s)

Dries De Witte

References

Alonso A, Bigirumurame T, Burzykowski T, Buyse M, Molenberghs G, Muchene L, Perualila NJ, Shkedy Z, Van der Elst W, et al. (2016). Applied surrogate endpoint evaluation methods with SAS and R. CRC Press New York

Examples

## Not run: 
data("prostate")
fit <- MetaAnalyticSurvCont(data = prostate, true = SURVTIME, trueind = SURVIND, surrog = PSA,
trt = TREAT, center = TRIAL, trial = TRIAL, patientid = PATID,
copula = "Hougaard", adjustment = "weighted")
summary(fit)
print(fit)
plot(fit)

## End(Not run)

[Package Surrogate version 3.3.0 Index]