plot_study: Plot ae development of study and sites highlighting at risk...

In openpharma/simaerep: Find Clinical Trial Sites Under-Reporting Adverse Events

Plot ae development of study and sites highlighting at risk sites.

Description

Most suitable visual representation of the AE under-reporting statistics.

Usage

plot_study(
  df_visit,
  df_site,
  df_eval,
  study,
  df_al = NULL,
  n_sites = 16,
  pval = FALSE,
  prob_col = "prob_low_prob_ur"
)

Arguments

df_visit	dataframe, created by sim_sites()
df_site	dataframe created by site_aggr()
df_eval	dataframe created by eval_sites()
study	study
df_al	dataframe containing study_id, site_number, alert_level_site, alert_level_study (optional), Default: NA
n_sites	integer number of most at risk sites, Default: 16
pval	logical show p-value, Default:FALSE
prob_col	character, denotes probability column, Default: "prob_low_prob_ur"

Details

Left panel shows mean AE reporting per site (lightblue and darkblue lines) against mean AE reporting of the entire study (golden line). Single sites are plotted in descending order by AE under-reporting probability on the right panel in which grey lines denote cumulative AE count of single patients. Grey dots in the left panel plot indicate sites that were picked for single plotting. AE under-reporting probability of dark blue lines crossed threshold of 95%. Numbers in the upper left corner indicate the ratio of patients that have been used for the analysis against the total number of patients. Patients that have not been on the study long enough to reach the evaluation point (visit_med75) will be ignored.

Value

ggplot

Examples

df_visit <- sim_test_data_study(n_pat = 1000, n_sites = 10,
    frac_site_with_ur = 0.2, ur_rate = 0.15, max_visit_sd = 8)

df_visit$study_id <- "A"
df_site <- site_aggr(df_visit)

df_sim_sites <- sim_sites(df_site, df_visit, r = 100)

df_eval <- eval_sites(df_sim_sites)

plot_study(df_visit, df_site, df_eval, study = "A")

openpharma/simaerep documentation built on Feb. 2, 2025, 12:04 a.m.