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PatientProfiler.rmd
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---
title: "Patient Profiler (Proof of Concept)"
date: "`r format(Sys.time(),format='%A %d %b %Y')`"
output:
flexdashboard::flex_dashboard:
vertical_layout: fill
self_contained: true
theme: default
source_code: "https://github.com/agstn/PatientProfiler"
---
```{r setup-main, include=FALSE}
# Knitr options
knitr::opts_chunk$set(echo = FALSE,
eval = TRUE,
warning = FALSE,
message = FALSE,
comment = NA,
cache = FALSE)
pacman::p_load(flexdashboard)
```
```{r setup-packages, include=FALSE}
pacman::p_load(tidyverse, rio, labelled)
pacman::p_load(patientProfilesVis, clinUtils)
pacman::p_load(plotly, sparkline)
pacman::p_load(reactable, reactablefmtr)
```
```{r setup-data, include=FALSE}
pathExampleDatasets <- list.files(
path = './dat/',
pattern = "*.xpt",
full.names = TRUE)
data <- loadDataADaMSDTM(files = pathExampleDatasets)
labelVarsADaM <- attr(data, "labelVars")
set.seed(123)
id <- c('01-701-1148',
'01-701-1192',
'01-701-1211',
'01-704-1445',
'01-718-1371',
'01-718-1427',
sample(data$ADSL$USUBJID, 40)) %>%
unique()
```
```{r derive-data, include=FALSE}
# subject data
subj <- data$ADSL %>%
filter(USUBJID %in% id) %>%
select(USUBJID, SEX, AGE, RACE, ETHNIC, BMIBL, TRT01P, DCDECOD) %>%
mutate(SEX_ICON = case_when(
SEX == "M" ~ "male",
SEX == "F" ~ "female")) %>%
mutate(SEX_COL = case_when(
SEX == "M" ~ '#01A6EA',
SEX == "F" ~ '#FFB1CB')) %>%
mutate(BMIBL_COL = case_when(
BMIBL > 30 ~ '#d7191c',
BMIBL > 25 ~ '#fdae61',
BMIBL > 18.5 ~ '#abd9e9',
TRUE ~ '#2c7bb6')) %>%
mutate(DCDECOD_COL = case_when(
DCDECOD == "COMPLETED" ~ '#238823',
DCDECOD == "DEATH" ~ '#d2222d',
TRUE ~ '#ffbf00'))
# treatment exposure
ex <- data$EX %>%
filter(USUBJID %in% id) %>%
mutate(USUBJID2 = USUBJID) %>%
group_nest(USUBJID) %>%
rowwise() %>%
mutate(
exPlots = list(
subjectProfileIntervalPlot(
data = data,
paramVar = c(
"EXTRT", "EXDOSE", "EXDOSU",
"EXDOSFRM", "EXDOSFRQ", "EXROUTE"
), # "EXTPT" if available
timeStartVar = "EXSTDY",
timeEndVar = "EXENDY",
# optional:
colorVar = "EXDOSFRM",
subjectVar = 'USUBJID2',
title = "Treatment exposure",
alpha = 0.8,
labelVars = labelVarsADaM)),
exPlots_ggplotly = list(
ggplotly(exPlots[[1]][['1']] +
labs(caption = NULL,
title = NULL) +
xlab('Analysis Start/End Relative Date')+
theme(legend.position='none'),
width = 700,
height = 200) %>%
config(displayModeBar = F)
)
)
# advese events
adae <- data$ADAE %>%
filter(USUBJID %in% id) %>%
mutate(USUBJID2 = USUBJID) %>%
group_nest(USUBJID) %>%
rowwise() %>%
mutate(
aePlots = list(
subjectProfileIntervalPlot(
data = data,
paramVar = "AETERM",
timeStartVar = "ASTDY",
timeEndVar = "AENDY",
colorVar = "AESEV",
subjectVar = 'USUBJID2',
labelVars = labelVarsADaM,
title = "Adverse events")
),
aePlots_ggplotly = list(
ggplotly(aePlots[[1]][['1']] +
labs(caption = NULL,
title = NULL) +
xlab('Analysis Start/End Relative Date')+
theme(legend.position='none'),
width = 700,
height = 300) %>%
config(displayModeBar = F)
)
)
# meds
adcm <- data$ADCM %>%
filter(USUBJID %in% id) %>%
mutate(USUBJID2 = USUBJID) %>%
group_nest(USUBJID) %>%
rowwise() %>%
mutate(
cmPlots = list(
subjectProfileIntervalPlot(
data = data,
paramVar = c(
"CMTRT",
"CMDOSE", "CMDOSU", "CMROUTE",
"CMDOSFRQ"),
timeStartVar = "ASTDY",
timeEndVar = "AENDY",
# optional:
paramGroupVar = "CMCLAS", # or CMINDC
colorVar = "CMCLAS", # or CMINDC
subjectVar = 'USUBJID2',
labelVars = labelVarsADaM,
title = "Concomitant medications",
# To zoom in axis scale in study time frame
# (to avoid scale is focused on negative pre-study time frame for CM)
timeTrans = getTimeTrans(type = "asinh-neg"),
alpha = 0.8,
timeAlign = FALSE
)
),
cmPlots_ggplotly = list(
ggplotly(cmPlots[[1]][['1']] +
labs(caption = NULL,
title = NULL) +
xlab('Analysis Start/End Relative Date')+
theme(legend.position='none'),
width = 700,
height = 400) %>%
config(displayModeBar = F)
)
)
# adlbc
adlbc_range <- data$ADLBC %>%
filter(USUBJID %in% id) %>%
filter(str_sub(PARAMCD,1,1) != "_" ) %>%
drop_na(AVAL) %>%
group_by(USUBJID, PARAMCD) %>%
summarise(N = n(),
A1LO = min(A1LO),
A1HI = max(A1HI),
MIN = min(AVAL),
MAX = max(AVAL)) %>%
group_by(PARAMCD) %>%
mutate(N_a = max(N),
MIN_a = min(MIN),
MAX_a = max(MAX))
adlbc <- data$ADLBC %>%
filter(USUBJID %in% id) %>%
filter(str_sub(PARAMCD,1,1) != "_" ) %>%
select(USUBJID, PARCAT1, PARAMCD, PARAM, AVAL) %>%
drop_na(AVAL) %>%
group_by(USUBJID, PARCAT1, PARAMCD, PARAM) %>%
summarise(spk = list(AVAL)) %>%
left_join(adlbc_range) %>%
rowwise() %>%
mutate(spk_l = list(
sparkline(spk,
height = 50,
width = 145,
fillColor= FALSE, # NO fill color
lineColor = '#404040', # LINE color (gray 25)
minSpotColor= 'red', # MIN value color
maxSpotColor= 'blue', # MAX value color
spotColor = '#404040', # value color
highlightSpotColor= '#404040',
highlightLineColor= '#404040',
spotRadius = 3, # SIZE pixels circles
normalRangeMin= A1LO,
normalRangeMax= A1HI,
normalRangeColor= '#e5e5e5',
chartRangeMin= MIN_a,
chartRangeMax= MAX_a,
chartRangeMinX= 1,
chartRangeMaxX= N_a)
), .after = spk
)
# adlbh
adlbh_range <- data$ADLBH %>%
filter(USUBJID %in% id) %>%
filter(str_sub(PARAMCD,1,1) != "_" ) %>%
drop_na(AVAL) %>%
group_by(USUBJID, PARAMCD) %>%
summarise(A1LO = min(A1LO),
A1HI = max(A1HI),
MIN = min(AVAL),
MAX = max(AVAL))
adlbh <- data$ADLBH %>%
filter(USUBJID %in% id) %>%
filter(str_sub(PARAMCD,1,1) != "_" ) %>%
select(USUBJID, PARCAT1, PARAMCD, PARAM, AVAL) %>%
drop_na(AVAL) %>%
group_by(USUBJID, PARCAT1, PARAMCD, PARAM) %>%
summarise(spk = list(AVAL)) %>%
left_join(adlbh_range)
# adlbhy
adlbhy_range <- data$ADLBHY %>%
filter(USUBJID %in% id) %>%
drop_na(AVAL) %>%
group_by(USUBJID, PARAMCD) %>%
summarise(A1LO = min(A1LO),
A1HI = max(A1HI),
MIN = min(AVAL),
MAX = max(AVAL))
adlbhy <- data$ADLBHY %>%
filter(USUBJID %in% id) %>%
select(USUBJID, PARCAT1, PARAMCD, PARAM, AVAL) %>%
drop_na(AVAL) %>%
group_by(USUBJID, PARCAT1, PARAMCD, PARAM) %>%
summarise(spk = list(AVAL)) %>%
left_join(adlbhy_range)
```
```{r data-combine}
d_all <- left_join(subj,
adlbc) %>%
group_nest(USUBJID, SEX, AGE, RACE, ETHNIC, BMIBL, TRT01P, DCDECOD, DCDECOD_COL, SEX_ICON, SEX_COL, BMIBL_COL,
.key = 'adlbc') %>%
left_join(adlbh) %>%
group_nest(USUBJID, SEX, AGE, RACE, ETHNIC, BMIBL, TRT01P, DCDECOD, DCDECOD_COL, SEX_ICON, SEX_COL, BMIBL_COL,
adlbc,
.key = 'adlbh') %>%
left_join(adlbhy) %>%
group_nest(USUBJID, SEX, AGE, RACE, ETHNIC, BMIBL, TRT01P, DCDECOD, DCDECOD_COL, SEX_ICON, SEX_COL, BMIBL_COL,
adlbc,
adlbh,
.key = 'adlbhy') %>%
left_join(ex %>% select(USUBJID, exPlots_ggplotly)) %>%
left_join(adae %>% select(USUBJID, aePlots_ggplotly)) %>%
left_join(adcm %>% select(USUBJID, cmPlots_ggplotly))
```
Table {data-orientation=rows data-icon="fa-list"}
=====================================
Row
-------------------------------------
```{r table-subject}
d_all %>%
reactable(.,
bordered = TRUE,
highlight = TRUE,
searchable = TRUE,
filterable = TRUE,
pagination = FALSE,
height = 850,
theme = fivethirtyeight(),
defaultColDef = colDef( vAlign = 'center',
width = 100),
columnGroups = list(
colGroup(name = 'demographics', columns = c("SEX","AGE","RACE","ETHNIC","BMIBL")),
colGroup(name = 'laboratory', columns = c("adlbc","adlbh","adlbhy")),
colGroup(name = 'trajectory', columns = c("exPlots_ggplotly","aePlots_ggplotly","cmPlots_ggplotly"))
),
columns = list(
USUBJID = colDef(width = 100,
style = list(fontWeight = 600)),
SEX_ICON = colDef(show = FALSE),
BMIBL_COL = colDef(show = FALSE),
SEX_COL = colDef(show = FALSE),
SEX = colDef(
width = 50,
align = 'center',
vAlign = 'center',
cell = icon_sets(.,
icon_ref = "SEX_ICON",
icon_position = "over",
icon_size = 28,
icon_color_ref = "SEX_COL")
),
BMIBL = colDef(
width = 125,
name = "BMI",
align = 'left',
html = TRUE,
header = JS('function(column) {return column.name + `<div style="color: #999">kg/m<sup>2</sup></div>`}'),
cell = data_bars(
.,
number_fmt = scales::number_format(accuracy = 0.1),
fill_color_ref = "BMIBL_COL",
text_position = "outside-base",
box_shadow = TRUE,
)
),
AGE = colDef(
width = 75,
align = 'center',
vAlign = 'center',
cell = gauge_chart(
.,
min_value = 51,
max_value = 89,
show_min_max = TRUE,
fill_color = 'gray25'
)
),
ETHNIC = colDef(show = FALSE),
RACE = colDef(
width = 200,
name = "RACE/ETHNICITY",
cell = merge_column(
.,
merged_name = "ETHNIC",
merged_position = 'below')
),
TRT01P = colDef(
width = 175,
),
DCDECOD_COL = colDef(show = FALSE),
DCDECOD = colDef(
width = 150,
name = 'DISPOSITION',
html = TRUE,
cell = pill_buttons(
data = .,
color_ref = 'DCDECOD_COL',
opacity = 0.9,
box_shadow = TRUE,
text_size = 10
)
),
cmPlots_ggplotly = colDef(
name = 'ADCM',
filterable = FALSE,
# cell = function() htmltools::tags$button("CM"),
cell = function(value){
if (length(value)>1) htmltools::tags$button("CM")
},
details = function(index) {
.$cmPlots_ggplotly[[index]]
}
),
exPlots_ggplotly = colDef(
name = 'EX',
filterable = FALSE,
cell = function(value){
if (length(value)>1) htmltools::tags$button("EX")
},
details = function(index) {
.$exPlots_ggplotly[[index]]
}
),
aePlots_ggplotly = colDef(
name = 'ADAE',
filterable = FALSE,
cell = function(value){
if (length(value)>1) htmltools::tags$button("AE")
},
details = function(index) {
.$aePlots_ggplotly[[index]]
}
),
adlbc = colDef(
name = 'ADLBC',
filterable = FALSE,
cell = function() htmltools::tags$button("CHEM"),
details = function(index){
reactable(.$adlbc[[index]],
bordered = TRUE,
highlight = TRUE,
searchable = TRUE,
filterable = TRUE,
pagination = FALSE,
height = 500,
theme = fivethirtyeight(),
columns = list(
PARCAT1 = colDef(show = FALSE),
PARAM = colDef(show = FALSE),
PARAMCD = colDef(
name = "PARAM",
width = 250,
vAlign = 'center',
cell = merge_column(
adlbc,
merged_name = "PARAM",
merged_position = 'below')),
spk_l = colDef(
name = '',
width = 150,
cell = function(value, index) adlbc$spk_l[[index]]
),
spk = colDef(show = FALSE),
N = colDef(show = FALSE),
N_a = colDef(show = FALSE),
MIN_a = colDef(show = FALSE),
MAX_a = colDef(show = FALSE),
A1HI = colDef(show = FALSE),
A1LO = colDef(
name = "Analy Range (LO-<u>HI</u>)",
html = TRUE,
width = 100,
cell = merge_column(
adlbc,
weight = 'normal',
merged_name = "A1HI",
merged_size = 14,
merged_color = 'black',
merged_decoration = 'underline',
spacing = 2,
)
),
MAX = colDef(show = FALSE),
MIN = colDef(
name = "Subj Range (LO-<u>HI</u>)",
html = TRUE,
width = 100,
cell = merge_column(
adlbc,
weight = 'normal',
merged_name = "MAX",
merged_size = 14,
merged_color = 'black',
merged_decoration = 'underline',
spacing = 3,
)
)
)
)
}
),
adlbh = colDef(
name = 'ADLBH',
filterable = FALSE,
cell = function() htmltools::tags$button("HEM"),
details = function(index){
reactable(.$adlbh[[index]],
bordered = TRUE,
highlight = TRUE,
searchable = TRUE,
filterable = TRUE,
pagination = FALSE,
height = 500,
theme = fivethirtyeight(),
columns = list(
PARCAT1 = colDef(show = FALSE),
PARAM = colDef(show = FALSE),
PARAMCD = colDef(
name = "PARAM",
width = 250,
vAlign = 'center',
cell = merge_column(
adlbc,
merged_name = "PARAM",
merged_position = 'below')),
spk = colDef(
name = '',
width = 150,
cell = react_sparkline(
.$adlbh[[index]],
highlight_points =
highlight_points(
first = 'gray',
min = "red",
max = "blue",
last = 'gray'),
labels = c('first','min','max','last'),
statline = "mean",
height = 50)
),
A1HI = colDef(show = FALSE),
A1LO = colDef(
name = "Analy Range (LO-<u>HI</u>)",
html = TRUE,
width = 100,
cell = merge_column(
adlbh,
weight = 'normal',
merged_name = "A1HI",
merged_size = 14,
merged_color = 'black',
merged_decoration = 'underline',
spacing = 2,
)
),
MAX = colDef(show = FALSE),
MIN = colDef(
name = "Subj Range (LO-<u>HI</u>)",
html = TRUE,
width = 100,
cell = merge_column(
adlbh,
weight = 'normal',
merged_name = "MAX",
merged_size = 14,
merged_color = 'black',
merged_decoration = 'underline',
spacing = 3,
)
)
)
)
}
),
adlbhy = colDef(
name = 'ADLBHY',
filterable = FALSE,
cell = function() htmltools::tags$button("HYLAW"),
details = function(index){
reactable(.$adlbhy[[index]],
bordered = TRUE,
highlight = TRUE,
searchable = TRUE,
filterable = TRUE,
pagination = FALSE,
height = 500,
theme = fivethirtyeight(),
columns = list(
PARCAT1 = colDef(show = FALSE),
PARAM = colDef(show = FALSE),
PARAMCD = colDef(
name = "PARAM",
width = 250,
vAlign = 'center',
cell = merge_column(
adlbhy,
merged_name = "PARAM",
merged_position = 'below')),
spk = colDef(
name = '',
width = 150,
cell = react_sparkline(
.$adlbhy[[index]],
highlight_points =
highlight_points(
first = 'gray',
min = "red",
max = "blue",
last = 'gray'),
labels = c('first','min','max','last'),
statline = "mean",
height = 50)
),
A1HI = colDef(show = FALSE),
A1LO = colDef(
name = "Analy Range (LO-<u>HI</u>)",
html = TRUE,
width = 100,
cell = merge_column(
adlbhy,
weight = 'normal',
merged_name = "A1HI",
merged_size = 14,
merged_color = 'black',
merged_decoration = 'underline',
spacing = 2,
)
),
MAX = colDef(show = FALSE),
MIN = colDef(
name = "Subj Range (LO-<u>HI</u>)",
html = TRUE,
width = 100,
cell = merge_column(
adlbhy,
weight = 'normal',
merged_name = "MAX",
merged_size = 14,
merged_color = 'black',
merged_decoration = 'underline',
spacing = 3,
)
)
)
)
}
)
)
)%>%
google_font(font_family = "Ubuntu Mono")
```
Definitions {data-orientation=rows data-icon="fa-file-pdf"}
=====================================
```{r out.height = "800px", out.width='1000px'}
knitr::include_graphics("./dat/dataguide.pdf")
```