vignettes/AdhereR-overview.R
In dffyfe/AdhereRFork: Adherence to Medications
## ---- echo=FALSE, message=FALSE, warning=FALSE, results='hide'----------------
# Various Rmarkdown output options:
# center figures and reduce their file size:
knitr::opts_chunk$set(fig.align = "center", dpi=100, dev="jpeg");
## ---- echo=TRUE, results='asis'-----------------------------------------------
# Load the AdhereR library:
library(AdhereR);
# Select the two patients with IDs 37 and 76 from the built-in dataset "med.events":
ExamplePats <- med.events[med.events$PATIENT_ID %in% c(37, 76), ];
# Display them as pretty markdown table:
knitr::kable(ExamplePats, caption = "<a name=\"Table-1\"></a>**Table 1.** Medication events for two example patients");
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-1\"></a>**Figure 1.** Medication histories - two example patients", fig.height=6, fig.width=8, out.width="100%"----
# Create an object "cma0" of the most basic CMA type, "CMA0":
cma0 <- CMA0(data=ExamplePats, # use the two selected patients
ID.colname="PATIENT_ID", # the name of the column containing the IDs
event.date.colname="DATE", # the name of the column containing the event date
event.duration.colname="DURATION", # the name of the column containing the duration
event.daily.dose.colname="PERDAY", # the name of the column containing the dosage
medication.class.colname="CATEGORY", # the name of the column containing the category
followup.window.start=0, # FUW start in days since earliest event
observation.window.start=182, # OW start in days since earliest event
observation.window.duration=365, # OW duration in days
date.format="%m/%d/%Y"); # date format (mm/dd/yyyy)
# Plot the object (CMA0 shows the actual event data only):
plot(cma0, # the object to plot
align.all.patients=TRUE); # align all patients for easier comparison
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-1a\"></a>**Figure 1 (a).** Same plot as in **Figure 1**, but also showing the daily doses as numbers and as line thickness", fig.height=6, fig.width=8, out.width="100%"----
# Same plot as above but also showing the daily doses:
plot(cma0, # the object to plot
print.dose=TRUE, plot.dose=TRUE,
align.all.patients=TRUE); # align all patients for easier comparison
## ---- echo=TRUE, results='asis'-----------------------------------------------
# Compute the treatment episodes for the two patients:
TEs3<- compute.treatment.episodes(ExamplePats,
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carryover.within.obs.window = TRUE, # carry-over into the OW
carry.only.for.same.medication = TRUE, # & only for same type
consider.dosage.change = TRUE, # dosage change starts new episode...
medication.change.means.new.treatment.episode = TRUE, # & type change
maximum.permissible.gap = 180, # & a gap longer than 180 days
maximum.permissible.gap.unit = "days", # unit for the above (days)
followup.window.start = 0, # 2-years FUW starts at earliest event
followup.window.start.unit = "days",
followup.window.duration = 365 * 2,
followup.window.duration.unit = "days",
date.format = "%m/%d/%Y");
knitr::kable(TEs3,
caption = "<a name=\"Table-2\"></a>**Table 2.** Example output `compute.treatment.episodes()` function");
## ---- echo=TRUE, results='asis'-----------------------------------------------
# Compute the treatment episodes for the two patients
# but now a change in medication type does not start a new episode:
TEs4<- compute.treatment.episodes(ExamplePats,
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carryover.within.obs.window = TRUE,
carry.only.for.same.medication = TRUE,
consider.dosage.change = TRUE,
medication.change.means.new.treatment.episode = FALSE, # here
maximum.permissible.gap = 180,
maximum.permissible.gap.unit = "days",
followup.window.start = 0,
followup.window.start.unit = "days",
followup.window.duration = 365 * 2,
followup.window.duration.unit = "days",
date.format = "%m/%d/%Y");
# Pretty print the events:
knitr::kable(TEs4,
caption = "<a name=\"Table-3\"></a>**Table 3.** Alternative scenario output `compute.treatment.episodes()` function");
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-2\"></a>**Figure 2.** Simple CMA 1", fig.height=5, fig.width=7, out.width="100%"----
# Create the CMA1 object with the given parameters:
cma1 <- CMA1(data=ExamplePats,
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
followup.window.start=0, observation.window.start=182,
observation.window.duration=365,
date.format="%m/%d/%Y");
# Display the summary:
cma1
# Display the estimated CMA table:
cma1$CMA
# and equivalently using an accessor function:
getCMA(cma1);
# Compute the CMA value for patient 76, as percentage rounded at 2 digits:
round(cma1$CMA[cma1$CMA$PATIENT_ID== 76, 2]*100, 2)
# Plot the CMA:
# The legend shows the actual duration, the days covered and gap days,
# the drug (medication) type, the FUW and OW, and the estimated CMA.
plot(cma1,
patients.to.plot=c("76"), # plot only patient 76
legend.x=520); # place the legend in a nice way
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-3\"></a>**Figure 3.** Simple CMA 2", fig.height=5, fig.width=7, out.width="100%"----
cma2 <- CMA2(data=ExamplePats, # we're estimating CMA2 now!
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
followup.window.start=0, observation.window.start=182,
observation.window.duration=365,
date.format="%m/%d/%Y");
plot(cma2,
patients.to.plot=c("76"),
show.legend=FALSE); # don't show legend to avoid clutter (see above)
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-4\"></a>**Figure 4.** Simple CMA 3", fig.height=5, fig.width=7, out.width="100%"----
cma3 <- CMA3(data=ExamplePats, # we're estimating CMA3 now!
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
followup.window.start=0, observation.window.start=182,
observation.window.duration=365,
date.format="%m/%d/%Y");
plot(cma3, patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-5\"></a>**Figure 5.** Simple CMA 4", fig.height=5, fig.width=7, out.width="100%"----
cma4 <- CMA4(data=ExamplePats, # we're estimating CMA4 now!
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
followup.window.start=0, observation.window.start=182,
observation.window.duration=365,
date.format="%m/%d/%Y");
plot(cma4,patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-6\"></a>**Figure 6.** Simple CMA 5", fig.height=5, fig.width=7, out.width="100%"----
cma5 <- CMA5(data=ExamplePats, # we're estimating CMA5 now!
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carry.only.for.same.medication=FALSE, # carry-over across medication types
consider.dosage.change=FALSE, # don't consider canges in dosage
followup.window.start=0, observation.window.start=182,
observation.window.duration=365,
date.format="%m/%d/%Y");
plot(cma5,patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-7\"></a>**Figure 7.** Simple CMA 6", fig.height=5, fig.width=7, out.width="100%"----
cma6 <- CMA6(data=ExamplePats, # we're estimating CMA6 now!
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carry.only.for.same.medication=FALSE,
consider.dosage.change=FALSE,
followup.window.start=0, observation.window.start=182,
observation.window.duration=365,
date.format="%m/%d/%Y");
plot(cma6,patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-1a\"></a>**Figure 7 (a).** Same plot as in **Figure 7**, but also showing the daily doses as numbers and as line thickness", fig.height=6, fig.width=8, out.width="100%"----
# Same plot as above but also showing the daily doses:
plot(cma6, # the object to plot
patients.to.plot=c("76"), # plot only patient 76
print.dose=TRUE, plot.dose=TRUE,
legend.x=520); # place the legend in a nice way
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-8\"></a>**Figure 8.** Simple CMA 7", fig.height=5, fig.width=7, out.width="100%"----
cma7 <- CMA7(data=ExamplePats, # we're estimating CMA7 now!
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carry.only.for.same.medication=FALSE,
consider.dosage.change=FALSE,
followup.window.start=0, observation.window.start=182,
observation.window.duration=365,
date.format="%m/%d/%Y");
plot(cma7, patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-9\"></a>**Figure 9.** Simple CMA 8", fig.height=5, fig.width=7, out.width="100%"----
cma8 <- CMA8(data=ExamplePats, # we're estimating CMA8 now!
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carry.only.for.same.medication=FALSE,
consider.dosage.change=FALSE,
followup.window.start=0, observation.window.start=374,
observation.window.duration=294,
date.format="%m/%d/%Y");
plot(cma8, patients.to.plot=c("76"), show.legend=FALSE);
# The value for patient 76, rounded at 2 digits
round(cma8$CMA[cma8$CMA$PATIENT_ID== 76, 2]*100, 2);
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-10\"></a>**Figure 10.** Simple CMA 9", fig.height=5, fig.width=7, out.width="100%"----
cma9 <- CMA9(data=ExamplePats, # we're estimating CMA9 now!
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carry.only.for.same.medication=FALSE,
consider.dosage.change=FALSE,
followup.window.start=0, observation.window.start=182,
observation.window.duration=365,
date.format="%m/%d/%Y");
plot(cma9, patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-11\"></a>**Figure 11.** CMA 9 per episode", fig.height=5, fig.width=7, out.width="100%", warning=FALSE----
cmaE <- CMA_per_episode(CMA="CMA9", # apply the simple CMA9 to each treatment episode
data=ExamplePats,
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carryover.within.obs.window = TRUE,
carry.only.for.same.medication = FALSE,
consider.dosage.change = FALSE, # conditions on treatment episodes
medication.change.means.new.treatment.episode = TRUE,
maximum.permissible.gap = 180,
maximum.permissible.gap.unit = "days",
followup.window.start=0,
followup.window.start.unit = "days",
followup.window.duration = 365 * 2,
followup.window.duration.unit = "days",
observation.window.start=0,
observation.window.start.unit = "days",
observation.window.duration=365*2,
observation.window.duration.unit = "days",
date.format="%m/%d/%Y",
parallel.backend="none",
parallel.threads=1);
# Summary:
cmaE;
# The CMA estimates table:
cmaE$CMA
getCMA(cmaE); # as above but using accessor function
# The values for patient 76 only, rounded at 2 digits:
round(cmaE$CMA[cmaE$CMA$PATIENT_ID== 76, 7]*100, 2);
# Plot:
plot(cmaE, patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-12\"></a>**Figure 12.** Sliding window CMA 9", fig.height=5, fig.width=7, out.width="100%"----
cmaW <- CMA_sliding_window(CMA.to.apply="CMA9", # apply the simple CMA9 to each sliding window
data=ExamplePats,
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carry.only.for.same.medication=FALSE,
consider.dosage.change=FALSE,
followup.window.start=0,
observation.window.start=0,
observation.window.duration=365*2,
sliding.window.start=0, # sliding windows definition
sliding.window.start.unit="days",
sliding.window.duration=120,
sliding.window.duration.unit="days",
sliding.window.step.duration=120,
sliding.window.step.unit="days",
date.format="%m/%d/%Y",
parallel.backend="none",
parallel.threads=1);
# Summary:
cmaW;
# The CMA estimates table:
cmaW$CMA
getCMA(cmaW); # as above but using accessor function
# The values for patient 76 only, rounded at 2 digits
round(cmaW$CMA[cmaW$CMA$PATIENT_ID== 76, 5]*100, 2);
# Plot:
plot(cmaW, patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=FALSE, fig.show='hold', fig.cap = "<a name=\"Figure-13\"></a>**Figure 13.** Sliding window CMA 9", fig.height=5, fig.width=7, out.width="100%"----
cmaW1 <- CMA_sliding_window(CMA.to.apply="CMA9",
data=ExamplePats,
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carry.only.for.same.medication=FALSE,
consider.dosage.change=FALSE,
followup.window.start=0,
observation.window.start=0,
observation.window.duration=365*2,
sliding.window.start=0, # different sliding windows
sliding.window.start.unit="days",
sliding.window.duration=120,
sliding.window.duration.unit="days",
sliding.window.step.duration=30,
sliding.window.step.unit="days",
date.format="%m/%d/%Y",
parallel.backend="none",
parallel.threads=1);
# Plot:
plot(cmaW1, patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=FALSE--------------------------------------------------------------
knitr::kable(head(med.events.ATC, n=5), row.names=FALSE,
caption="First 5 lines of the `med.events.ATC` dataset.");
## ---- eval=FALSE--------------------------------------------------------------
# event_durations <- compute_event_durations(disp.data = durcomp.dispensing,
# presc.data = durcomp.prescribing,
# special.periods.data = durcomp.hospitalisation,
# ID.colname = "ID",
# presc.date.colname = "DATE.PRESC",
# disp.date.colname = "DATE.DISP",
# medication.class.colnames = c("ATC.CODE", "UNIT", "FORM"),
# total.dose.colname = "TOTAL.DOSE",
# presc.daily.dose.colname = "DAILY.DOSE",
# presc.duration.colname = "PRESC.DURATION",
# visit.colname = "VISIT",
# split.on.dosage.change = TRUE,
# force.init.presc = TRUE,
# force.presc.renew = TRUE,
# trt.interruption = "continue",
# special.periods.method = "continue",
# date.format = "%Y-%m-%d",
# suppress.warnings = FALSE,
# return.data.table = FALSE);
# med.events.ATC <- event_durations$event_durations[ !is.na(event_durations$event_durations$DURATION) &
# event_durations$event_durations$DURATION > 0,
# c("ID", "DISP.START", "DURATION", "DAILY.DOSE", "ATC.CODE")];
# names(med.events.ATC) <- c("PATIENT_ID", "DATE", "DURATION", "PERDAY", "CATEGORY");
# # Groups from the ATC codes:
# sort(unique(med.events.ATC$CATEGORY)); # all the ATC codes in the data
# # Level 1:
# med.events.ATC$CATEGORY_L1 <- vapply(substr(med.events.ATC$CATEGORY,1,1), switch, character(1),
# "A"="ALIMENTARY TRACT AND METABOLISM",
# "B"="BLOOD AND BLOOD FORMING ORGANS",
# "J"="ANTIINFECTIVES FOR SYSTEMIC USE",
# "R"="RESPIRATORY SYSTEM",
# "OTHER");
# # Level 2:
# med.events.ATC$CATEGORY_L2 <- vapply(substr(med.events.ATC$CATEGORY,1,3), switch, character(1),
# "A02"="DRUGS FOR ACID RELATED DISORDERS",
# "A05"="BILE AND LIVER THERAPY",
# "A09"="DIGESTIVES, INCL. ENZYMES",
# "A10"="DRUGS USED IN DIABETES",
# "A11"="VITAMINS",
# "A12"="MINERAL SUPPLEMENTS",
# "B02"="ANTIHEMORRHAGICS",
# "J01"="ANTIBACTERIALS FOR SYSTEMIC USE",
# "J02"="ANTIMYCOTICS FOR SYSTEMIC USE",
# "R03"="DRUGS FOR OBSTRUCTIVE AIRWAY DISEASES",
# "R05"="COUGH AND COLD PREPARATIONS",
# "OTHER");
## ----eval=FALSE---------------------------------------------------------------
# med.groups <- c("Vitamins" = "(CATEGORY_L2 == 'VITAMINS')",
# "VitaResp" = "({Vitamins} | CATEGORY_L1 == 'RESPIRATORY SYSTEM')",
# "VitaShort" = "({Vitamins} & DURATION <= 30)",
# "VitELow" = "(CATEGORY == 'A11HA03' & PERDAY <= 500)",
# "VitaComb" = "({VitaShort} | {VitELow})",
# "NotVita" = "(!{Vitamins})");
## ---- echo=FALSE--------------------------------------------------------------
knitr::kable(head(med.events.ATC[med.events.ATC$CATEGORY_L2 == 'VITAMINS',], n=5), row.names=FALSE,
caption="First 5 events in `med.events.ATC` corresponding to the *Vitamins* medication group.");
## ---- echo=FALSE--------------------------------------------------------------
knitr::kable(head(med.events.ATC[med.events.ATC$CATEGORY_L2 == 'VITAMINS' | med.events.ATC$CATEGORY_L1 == 'RESPIRATORY SYSTEM',], n=5), row.names=FALSE,
caption="First 5 events in `med.events.ATC` corresponding to the *VitaResp* medication group.");
dffyfe/AdhereRFork documentation built on Sept. 13, 2023, 8:50 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
## ---- echo=FALSE, message=FALSE, warning=FALSE, results='hide'----------------
# Various Rmarkdown output options:
# center figures and reduce their file size:
knitr::opts_chunk$set(fig.align = "center", dpi=100, dev="jpeg");
## ---- echo=TRUE, results='asis'-----------------------------------------------
# Load the AdhereR library:
library(AdhereR);
# Select the two patients with IDs 37 and 76 from the built-in dataset "med.events":
ExamplePats <- med.events[med.events$PATIENT_ID %in% c(37, 76), ];
# Display them as pretty markdown table:
knitr::kable(ExamplePats, caption = "<a name=\"Table-1\"></a>**Table 1.** Medication events for two example patients");
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-1\"></a>**Figure 1.** Medication histories - two example patients", fig.height=6, fig.width=8, out.width="100%"----
# Create an object "cma0" of the most basic CMA type, "CMA0":
cma0 <- CMA0(data=ExamplePats, # use the two selected patients
ID.colname="PATIENT_ID", # the name of the column containing the IDs
event.date.colname="DATE", # the name of the column containing the event date
event.duration.colname="DURATION", # the name of the column containing the duration
event.daily.dose.colname="PERDAY", # the name of the column containing the dosage
medication.class.colname="CATEGORY", # the name of the column containing the category
followup.window.start=0, # FUW start in days since earliest event
observation.window.start=182, # OW start in days since earliest event
observation.window.duration=365, # OW duration in days
date.format="%m/%d/%Y"); # date format (mm/dd/yyyy)
# Plot the object (CMA0 shows the actual event data only):
plot(cma0, # the object to plot
align.all.patients=TRUE); # align all patients for easier comparison
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-1a\"></a>**Figure 1 (a).** Same plot as in **Figure 1**, but also showing the daily doses as numbers and as line thickness", fig.height=6, fig.width=8, out.width="100%"----
# Same plot as above but also showing the daily doses:
plot(cma0, # the object to plot
print.dose=TRUE, plot.dose=TRUE,
align.all.patients=TRUE); # align all patients for easier comparison
## ---- echo=TRUE, results='asis'-----------------------------------------------
# Compute the treatment episodes for the two patients:
TEs3<- compute.treatment.episodes(ExamplePats,
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carryover.within.obs.window = TRUE, # carry-over into the OW
carry.only.for.same.medication = TRUE, # & only for same type
consider.dosage.change = TRUE, # dosage change starts new episode...
medication.change.means.new.treatment.episode = TRUE, # & type change
maximum.permissible.gap = 180, # & a gap longer than 180 days
maximum.permissible.gap.unit = "days", # unit for the above (days)
followup.window.start = 0, # 2-years FUW starts at earliest event
followup.window.start.unit = "days",
followup.window.duration = 365 * 2,
followup.window.duration.unit = "days",
date.format = "%m/%d/%Y");
knitr::kable(TEs3,
caption = "<a name=\"Table-2\"></a>**Table 2.** Example output `compute.treatment.episodes()` function");
## ---- echo=TRUE, results='asis'-----------------------------------------------
# Compute the treatment episodes for the two patients
# but now a change in medication type does not start a new episode:
TEs4<- compute.treatment.episodes(ExamplePats,
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carryover.within.obs.window = TRUE,
carry.only.for.same.medication = TRUE,
consider.dosage.change = TRUE,
medication.change.means.new.treatment.episode = FALSE, # here
maximum.permissible.gap = 180,
maximum.permissible.gap.unit = "days",
followup.window.start = 0,
followup.window.start.unit = "days",
followup.window.duration = 365 * 2,
followup.window.duration.unit = "days",
date.format = "%m/%d/%Y");
# Pretty print the events:
knitr::kable(TEs4,
caption = "<a name=\"Table-3\"></a>**Table 3.** Alternative scenario output `compute.treatment.episodes()` function");
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-2\"></a>**Figure 2.** Simple CMA 1", fig.height=5, fig.width=7, out.width="100%"----
# Create the CMA1 object with the given parameters:
cma1 <- CMA1(data=ExamplePats,
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
followup.window.start=0, observation.window.start=182,
observation.window.duration=365,
date.format="%m/%d/%Y");
# Display the summary:
cma1
# Display the estimated CMA table:
cma1$CMA
# and equivalently using an accessor function:
getCMA(cma1);
# Compute the CMA value for patient 76, as percentage rounded at 2 digits:
round(cma1$CMA[cma1$CMA$PATIENT_ID== 76, 2]*100, 2)
# Plot the CMA:
# The legend shows the actual duration, the days covered and gap days,
# the drug (medication) type, the FUW and OW, and the estimated CMA.
plot(cma1,
patients.to.plot=c("76"), # plot only patient 76
legend.x=520); # place the legend in a nice way
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-3\"></a>**Figure 3.** Simple CMA 2", fig.height=5, fig.width=7, out.width="100%"----
cma2 <- CMA2(data=ExamplePats, # we're estimating CMA2 now!
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
followup.window.start=0, observation.window.start=182,
observation.window.duration=365,
date.format="%m/%d/%Y");
plot(cma2,
patients.to.plot=c("76"),
show.legend=FALSE); # don't show legend to avoid clutter (see above)
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-4\"></a>**Figure 4.** Simple CMA 3", fig.height=5, fig.width=7, out.width="100%"----
cma3 <- CMA3(data=ExamplePats, # we're estimating CMA3 now!
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
followup.window.start=0, observation.window.start=182,
observation.window.duration=365,
date.format="%m/%d/%Y");
plot(cma3, patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-5\"></a>**Figure 5.** Simple CMA 4", fig.height=5, fig.width=7, out.width="100%"----
cma4 <- CMA4(data=ExamplePats, # we're estimating CMA4 now!
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
followup.window.start=0, observation.window.start=182,
observation.window.duration=365,
date.format="%m/%d/%Y");
plot(cma4,patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-6\"></a>**Figure 6.** Simple CMA 5", fig.height=5, fig.width=7, out.width="100%"----
cma5 <- CMA5(data=ExamplePats, # we're estimating CMA5 now!
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carry.only.for.same.medication=FALSE, # carry-over across medication types
consider.dosage.change=FALSE, # don't consider canges in dosage
followup.window.start=0, observation.window.start=182,
observation.window.duration=365,
date.format="%m/%d/%Y");
plot(cma5,patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-7\"></a>**Figure 7.** Simple CMA 6", fig.height=5, fig.width=7, out.width="100%"----
cma6 <- CMA6(data=ExamplePats, # we're estimating CMA6 now!
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carry.only.for.same.medication=FALSE,
consider.dosage.change=FALSE,
followup.window.start=0, observation.window.start=182,
observation.window.duration=365,
date.format="%m/%d/%Y");
plot(cma6,patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-1a\"></a>**Figure 7 (a).** Same plot as in **Figure 7**, but also showing the daily doses as numbers and as line thickness", fig.height=6, fig.width=8, out.width="100%"----
# Same plot as above but also showing the daily doses:
plot(cma6, # the object to plot
patients.to.plot=c("76"), # plot only patient 76
print.dose=TRUE, plot.dose=TRUE,
legend.x=520); # place the legend in a nice way
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-8\"></a>**Figure 8.** Simple CMA 7", fig.height=5, fig.width=7, out.width="100%"----
cma7 <- CMA7(data=ExamplePats, # we're estimating CMA7 now!
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carry.only.for.same.medication=FALSE,
consider.dosage.change=FALSE,
followup.window.start=0, observation.window.start=182,
observation.window.duration=365,
date.format="%m/%d/%Y");
plot(cma7, patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-9\"></a>**Figure 9.** Simple CMA 8", fig.height=5, fig.width=7, out.width="100%"----
cma8 <- CMA8(data=ExamplePats, # we're estimating CMA8 now!
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carry.only.for.same.medication=FALSE,
consider.dosage.change=FALSE,
followup.window.start=0, observation.window.start=374,
observation.window.duration=294,
date.format="%m/%d/%Y");
plot(cma8, patients.to.plot=c("76"), show.legend=FALSE);
# The value for patient 76, rounded at 2 digits
round(cma8$CMA[cma8$CMA$PATIENT_ID== 76, 2]*100, 2);
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-10\"></a>**Figure 10.** Simple CMA 9", fig.height=5, fig.width=7, out.width="100%"----
cma9 <- CMA9(data=ExamplePats, # we're estimating CMA9 now!
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carry.only.for.same.medication=FALSE,
consider.dosage.change=FALSE,
followup.window.start=0, observation.window.start=182,
observation.window.duration=365,
date.format="%m/%d/%Y");
plot(cma9, patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-11\"></a>**Figure 11.** CMA 9 per episode", fig.height=5, fig.width=7, out.width="100%", warning=FALSE----
cmaE <- CMA_per_episode(CMA="CMA9", # apply the simple CMA9 to each treatment episode
data=ExamplePats,
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carryover.within.obs.window = TRUE,
carry.only.for.same.medication = FALSE,
consider.dosage.change = FALSE, # conditions on treatment episodes
medication.change.means.new.treatment.episode = TRUE,
maximum.permissible.gap = 180,
maximum.permissible.gap.unit = "days",
followup.window.start=0,
followup.window.start.unit = "days",
followup.window.duration = 365 * 2,
followup.window.duration.unit = "days",
observation.window.start=0,
observation.window.start.unit = "days",
observation.window.duration=365*2,
observation.window.duration.unit = "days",
date.format="%m/%d/%Y",
parallel.backend="none",
parallel.threads=1);
# Summary:
cmaE;
# The CMA estimates table:
cmaE$CMA
getCMA(cmaE); # as above but using accessor function
# The values for patient 76 only, rounded at 2 digits:
round(cmaE$CMA[cmaE$CMA$PATIENT_ID== 76, 7]*100, 2);
# Plot:
plot(cmaE, patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=TRUE, fig.show='hold', fig.cap = "<a name=\"Figure-12\"></a>**Figure 12.** Sliding window CMA 9", fig.height=5, fig.width=7, out.width="100%"----
cmaW <- CMA_sliding_window(CMA.to.apply="CMA9", # apply the simple CMA9 to each sliding window
data=ExamplePats,
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carry.only.for.same.medication=FALSE,
consider.dosage.change=FALSE,
followup.window.start=0,
observation.window.start=0,
observation.window.duration=365*2,
sliding.window.start=0, # sliding windows definition
sliding.window.start.unit="days",
sliding.window.duration=120,
sliding.window.duration.unit="days",
sliding.window.step.duration=120,
sliding.window.step.unit="days",
date.format="%m/%d/%Y",
parallel.backend="none",
parallel.threads=1);
# Summary:
cmaW;
# The CMA estimates table:
cmaW$CMA
getCMA(cmaW); # as above but using accessor function
# The values for patient 76 only, rounded at 2 digits
round(cmaW$CMA[cmaW$CMA$PATIENT_ID== 76, 5]*100, 2);
# Plot:
plot(cmaW, patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=FALSE, fig.show='hold', fig.cap = "<a name=\"Figure-13\"></a>**Figure 13.** Sliding window CMA 9", fig.height=5, fig.width=7, out.width="100%"----
cmaW1 <- CMA_sliding_window(CMA.to.apply="CMA9",
data=ExamplePats,
ID.colname="PATIENT_ID",
event.date.colname="DATE",
event.duration.colname="DURATION",
event.daily.dose.colname="PERDAY",
medication.class.colname="CATEGORY",
carry.only.for.same.medication=FALSE,
consider.dosage.change=FALSE,
followup.window.start=0,
observation.window.start=0,
observation.window.duration=365*2,
sliding.window.start=0, # different sliding windows
sliding.window.start.unit="days",
sliding.window.duration=120,
sliding.window.duration.unit="days",
sliding.window.step.duration=30,
sliding.window.step.unit="days",
date.format="%m/%d/%Y",
parallel.backend="none",
parallel.threads=1);
# Plot:
plot(cmaW1, patients.to.plot=c("76"), show.legend=FALSE);
## ---- echo=FALSE--------------------------------------------------------------
knitr::kable(head(med.events.ATC, n=5), row.names=FALSE,
caption="First 5 lines of the `med.events.ATC` dataset.");
## ---- eval=FALSE--------------------------------------------------------------
# event_durations <- compute_event_durations(disp.data = durcomp.dispensing,
# presc.data = durcomp.prescribing,
# special.periods.data = durcomp.hospitalisation,
# ID.colname = "ID",
# presc.date.colname = "DATE.PRESC",
# disp.date.colname = "DATE.DISP",
# medication.class.colnames = c("ATC.CODE", "UNIT", "FORM"),
# total.dose.colname = "TOTAL.DOSE",
# presc.daily.dose.colname = "DAILY.DOSE",
# presc.duration.colname = "PRESC.DURATION",
# visit.colname = "VISIT",
# split.on.dosage.change = TRUE,
# force.init.presc = TRUE,
# force.presc.renew = TRUE,
# trt.interruption = "continue",
# special.periods.method = "continue",
# date.format = "%Y-%m-%d",
# suppress.warnings = FALSE,
# return.data.table = FALSE);
# med.events.ATC <- event_durations$event_durations[ !is.na(event_durations$event_durations$DURATION) &
# event_durations$event_durations$DURATION > 0,
# c("ID", "DISP.START", "DURATION", "DAILY.DOSE", "ATC.CODE")];
# names(med.events.ATC) <- c("PATIENT_ID", "DATE", "DURATION", "PERDAY", "CATEGORY");
# # Groups from the ATC codes:
# sort(unique(med.events.ATC$CATEGORY)); # all the ATC codes in the data
# # Level 1:
# med.events.ATC$CATEGORY_L1 <- vapply(substr(med.events.ATC$CATEGORY,1,1), switch, character(1),
# "A"="ALIMENTARY TRACT AND METABOLISM",
# "B"="BLOOD AND BLOOD FORMING ORGANS",
# "J"="ANTIINFECTIVES FOR SYSTEMIC USE",
# "R"="RESPIRATORY SYSTEM",
# "OTHER");
# # Level 2:
# med.events.ATC$CATEGORY_L2 <- vapply(substr(med.events.ATC$CATEGORY,1,3), switch, character(1),
# "A02"="DRUGS FOR ACID RELATED DISORDERS",
# "A05"="BILE AND LIVER THERAPY",
# "A09"="DIGESTIVES, INCL. ENZYMES",
# "A10"="DRUGS USED IN DIABETES",
# "A11"="VITAMINS",
# "A12"="MINERAL SUPPLEMENTS",
# "B02"="ANTIHEMORRHAGICS",
# "J01"="ANTIBACTERIALS FOR SYSTEMIC USE",
# "J02"="ANTIMYCOTICS FOR SYSTEMIC USE",
# "R03"="DRUGS FOR OBSTRUCTIVE AIRWAY DISEASES",
# "R05"="COUGH AND COLD PREPARATIONS",
# "OTHER");
## ----eval=FALSE---------------------------------------------------------------
# med.groups <- c("Vitamins" = "(CATEGORY_L2 == 'VITAMINS')",
# "VitaResp" = "({Vitamins} | CATEGORY_L1 == 'RESPIRATORY SYSTEM')",
# "VitaShort" = "({Vitamins} & DURATION <= 30)",
# "VitELow" = "(CATEGORY == 'A11HA03' & PERDAY <= 500)",
# "VitaComb" = "({VitaShort} | {VitELow})",
# "NotVita" = "(!{Vitamins})");
## ---- echo=FALSE--------------------------------------------------------------
knitr::kable(head(med.events.ATC[med.events.ATC$CATEGORY_L2 == 'VITAMINS',], n=5), row.names=FALSE,
caption="First 5 events in `med.events.ATC` corresponding to the *Vitamins* medication group.");
## ---- echo=FALSE--------------------------------------------------------------
knitr::kable(head(med.events.ATC[med.events.ATC$CATEGORY_L2 == 'VITAMINS' | med.events.ATC$CATEGORY_L1 == 'RESPIRATORY SYSTEM',], n=5), row.names=FALSE,
caption="First 5 events in `med.events.ATC` corresponding to the *VitaResp* medication group.");
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.