1-dashboard.Rmd

---
title: "Adverse Events for Keytruda"
output: 
  flexdashboard::flex_dashboard:
    orientation: row
---

```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse)
library(openfda)
library(ggthemes)
library(gt)

get_adverse <- function(gender, brand_name) {
  fda_query("/drug/event.json") %>%
    fda_filter("patient.drug.openfda.brand_name", brand_name) %>% 
    fda_filter("patient.patientsex", gender) %>% 
    fda_count("patient.reaction.reactionmeddrapt.exact") %>% 
    fda_exec()
}

total_events<- function(brand_name){
  fda_query("/drug/event.json") %>%
    fda_filter("patient.drug.openfda.brand_name", brand_name) %>% 
    fda_count("patient.reaction.reactionmeddrapt.exact") %>% 
    fda_exec()
}

serious_events<- function(brand_name){
  fda_query("/drug/event.json") %>%
    fda_filter("patient.drug.openfda.brand_name", brand_name) %>% 
    fda_count("serious") %>% 
    fda_exec()
}

drug<- 'Keytruda'
female<-get_adverse(2, drug) %>% mutate(sex = 'female')
male<-get_adverse(1, drug)%>% mutate(sex = 'male')

all<- total_events(drug) 
total_count<- sum(all$count)
serious<-serious_events(drug) %>% filter(term==1) %>% pull(count)
```

Row
-----------------------------------------------------------------------

### Total Events Reported

```{r}
valueBox(total_count)
```

### Serious Events

```{r}

valueBox(serious)
```

Row
-----------------------------------------------------------------------

### All Events 
```{r}
all %>% 
  top_n(10, count) %>%
ggplot()+
  geom_bar(aes(x=reorder(term, count), y=count), stat='identity', fill ="#3686D3")+
  coord_flip()+ 
  theme_tufte()+
  xlab('')+
  ylab('Events Reported') 

```

### Events By Sex

```{r}
rbind(male,female) %>%  
  mutate(term=str_to_title(term)) %>% 
  pivot_wider(names_from=sex, values_from=count) %>% 
  mutate(Total=female+male) %>% 
  top_n(10, Total) %>% 
  gt(rowname_col="term") %>% tab_header(
    title = md("Adverse Events"),
    subtitle = "The top ten most reported events"
) %>% tab_source_note("All data queried from openFDA") %>% 
  tab_stubhead(label= 'Patient Reaction') %>% 
  tab_spanner(label = "By sex",
              columns = c(female, male)) %>% 
  tab_spanner(label= 'Total Cases',
              columns = Total) %>% 
    fmt_number(columns = c(female, male, Total), sep_mark = ',', decimals=0) %>% 
  cols_label(Total = '',
             female = 'Female',
             male= 'Male')
```