Nothing
## ---- eval = FALSE-------------------------------------------------------
# install.packages("devtools")
# library(devtools)
# install_github("sachsmc/rclinicaltrials")
## ------------------------------------------------------------------------
library(rclinicaltrials)
library(ggplot2)
library(dplyr)
z <- clinicaltrials_search(query = 'lime+disease')
str(z)
## ------------------------------------------------------------------------
clinicaltrials_count(query = "myeloma")
clinicaltrials_count(query = "29485tksrw@")
## ------------------------------------------------------------------------
clinicaltrials_count(query = c("type=Intr", "cond=cancer"))
## ------------------------------------------------------------------------
head(advanced_search_terms)
## ------------------------------------------------------------------------
y <- clinicaltrials_download(query = 'myeloma', count = 10, include_results = TRUE)
str(y)
## ------------------------------------------------------------------------
melanom <- clinicaltrials_search(query = c("cond=melanoma", "phase=2",
"type=Intr", "rslt=With"),
count = 1e6)
nrow(melanom)
table(melanom$status.text)
melanom2 <- clinicaltrials_search(query = list(cond = "melanoma", phase = "2",
type = "Intr", rslt = "With"),
count = 1e6)
nrow(melanom)
## ----check, eval = FALSE-------------------------------------------------
# melanom_information <- clinicaltrials_download(query = c("cond=melanoma", "phase=2",
# "type=Intr", "rslt=With"),
# count = 1e6, include_results = TRUE)
## ----reup, include = FALSE-----------------------------------------------
load("melanom_info.RData")
## ----fig, fig.width = 6.5, fig.height = 5--------------------------------
summary(melanom_information$study_results$baseline_data)
gend_data <- subset(melanom_information$study_results$baseline_data,
title == "Gender" & arm != "Total")
gender_counts <- gend_data %>% group_by(nct_id, subtitle) %>%
do( data.frame(
count = sum(as.numeric(paste(.$value)), na.rm = TRUE)
))
dates <- melanom_information$study_information$study_info[, c("nct_id", "start_date")]
dates$year <- sapply(strsplit(paste(dates$start_date), " "), function(d) as.numeric(d[2]))
counts <- merge(gender_counts, dates, by = "nct_id")
cts <- counts %>% group_by(year, subtitle) %>%
summarize(count = sum(count))
colnames(cts)[2] <- "Gender"
ggplot(cts, aes(x = year, y = cumsum(count), color = Gender)) +
geom_line() + geom_point() +
labs(title = "Cumulative enrollment into Phase III, \n interventional trials in Melanoma, by gender") +
scale_y_continuous("Cumulative Enrollment")
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