CONSORT Analysis.Rmd

---
title: 'Data Safety Monitoring Report for STU000201005, A Randomized Controlled Trial of Drug XYZ Among Adults'
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```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)
library(tableone)
library(knitr)
options(digits=2)

ID <- c(1001,1002,1003,1004,1005,1006,1007,1008,1009,1010) 
Sex <- c("Male","Female","Male","Male","Female","Male","Female","Female","Female","Male") 
Age <- c(55,45,64,56,43,63,59,62,51,49) 
Screen <- c(1,1,1,1,1,1,1,1,1,0)
Randomize <-c(1,0,1,1,1,0,1,1,1,NA)
Treatment <- c(0,NA,0,1,1,NA,1,0,0,NA)

Enrollment <- data.frame(ID,Sex,Age,Screen,Randomize,Treatment) 
```

\usepackage[utf8]

**Principal Investigator:** Mary Smith, MD

**Protocol Synopsis:** This is a randomized controlled trial comparing the safety of Drug XYZ among adult participants. The primary outcome is any occurence of pre-specified Adverse Events (AEs) or Serious Adverse Events (SAEs).

**Study Status:** The study is currently open to enrollment.   
Study Inititation: July 28, 2016.   
Date of Report: `r format(Sys.Date(), '%B %d, %Y')`  

```{r, echo=FALSE}
#Enrollment <- subset(Enrollment, Enrollment$ID != 1007)
#Enrollment <- subset(Enrollment, Enrollment$ID != 1003)

#1. No. Patients Identified for Screening
enrolled <- nrow(Enrollment)

#2. No. Patients screened
screened <- sum(na.omit(Enrollment$Screen) == 1)

#3. No. Patients Pending screening
notscreened <-  sum(na.omit(Enrollment$Screen) == 0)

#4. No. Patients Randomized
randomized <- sum(na.omit(Enrollment$Randomize) == 1)

#5. No. Patients Pending Randomization
notrandomicated <- sum(na.omit(Enrollment$Randomize) == 0)

#6. No. Patients in Treatment Group
treatment <- sum(na.omit(Enrollment$Treatment) == 1)

#7. No. Patients in Control Group
control <- sum(na.omit(Enrollment$Treatment) == 0)
```
**Recruitment and Participant Status:**   
Participants Consented: `r enrolled`  
Participants Screened: `r screened`  
Participants Randomized: `r randomized`  
Participants In Treatment Group: `r treatment`  
Participants in Control Group: `r control`  

```{r, echo=FALSE}
#Create descriptives table of age and gender by treatment group
TableOne <- CreateTableOne(data = Enrollment, vars=c("Sex","Age"), strata= "Treatment")
Table1 <- print(TableOne, quote = FALSE, noSpaces = TRUE, printToggle = FALSE, test=FALSE,explain=FALSE,showAllLevels = TRUE)
```

**Table 1.** Participant Characteristics
```{r, echo=FALSE, comment=NA, size = 'tiny'}
#8. Output Table 1
knitr::kable(Table1)
```

**Particiants Pending Screening:** The following particiapnts are pending screening.
```{r, echo=FALSE}
#9. Print list of patients pending screening
print(Enrollment[Enrollment$Screen == 0,1])
```