multinma (version 0.8.0)

set_agd_surv: Set up aggregate survival data

Description

Set up a network containing aggregate survival data (AgD) in the form of event/censoring times (e.g. reconstructed from digitized Kaplan-Meier curves) and covariate summary statistics from each study. Multiple data sources may be combined once created using combine_network().

Usage

set_agd_surv(
  data,
  study,
  trt,
  Surv,
  covariates = NULL,
  trt_ref = NULL,
  trt_class = NULL
)

Value

An object of class nma_data

Arguments

data

a data frame

study

column of data specifying the studies, coded using integers, strings, or factors

trt

column of data specifying treatments, coded using integers, strings, or factors

Surv

column of data specifying a survival or time-to-event outcome, using the Surv() function. Right/left/interval censoring and left truncation (delayed entry) are supported.

covariates

data frame of covariate summary statistics for each study or study arm, with corresponding study and trt columns to match to those in data

trt_ref

reference treatment for the network, as a single integer, string, or factor. If not specified, a reasonable well-connected default will be chosen (see details).

trt_class

column of data specifying treatment classes, coded using integers, strings, or factors. By default, no classes are specified.

Details

By default, trt_ref = NULL and a network reference treatment will be chosen that attempts to maximise computational efficiency and stability. If an alternative reference treatment is chosen and the model runs slowly or has low effective sample size (ESS) this may be the cause - try letting the default reference treatment be used instead. Regardless of which treatment is used as the network reference at the model fitting stage, results can be transformed afterwards: see the trt_ref argument of relative_effects() and predict.stan_nma().

All arguments specifying columns of data accept the following:

• A column name as a character string, e.g. study = "studyc"

• A bare column name, e.g. study = studyc

• dplyr::mutate() style semantics for inline variable transformations, e.g. study = paste(author, year)

See Also

set_ipd() for individual patient data, set_agd_contrast() for contrast-based aggregate data, and combine_network() for combining several data sources in one network.

print.nma_data() for the print method displaying details of the network, and plot.nma_data() for network plots.

Examples

## Newly diagnosed multiple myeloma

head(ndmm_agd)  # Reconstructed Kaplan-Meier data
ndmm_agd_covs   # Summary covariate information on each arm

set_agd_surv(ndmm_agd,
             study = studyf,
             trt = trtf,
             Surv = Surv(eventtime, status),
             covariates = ndmm_agd_covs)