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AMR/data-raw/reproduction_of_antibiotics.R

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# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis #
# #
# SOURCE #
# https://gitlab.com/msberends/AMR #
# #
# LICENCE #
# (c) 2018-2020 Berends MS, Luz CF et al. #
# #
# This R package is free software; you can freely use and distribute #
# it for both personal and commercial purposes under the terms of the #
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
# the Free Software Foundation. #
# #
# We created this package for both routine data analysis and academic #
# research and it was publicly released in the hope that it will be #
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
# ==================================================================== #
library(dplyr)
# got EARS-Net codes (= ECDC/WHO codes) from here:
# Installed WHONET 2019 software on Windows (http://www.whonet.org/software.html),
# opened C:\WHONET\Codes\WHONETCodes.mdb in MS Access
# and exported table 'DRGLST' to MS Excel
library(readxl)
DRGLST <- read_excel("DRGLST.xlsx")
abx <- DRGLST %>%
select(ab = WHON5_CODE,
name = ANTIBIOTIC) %>%
# remove the ones without WHONET code
filter(!is.na(ab)) %>%
distinct(name, .keep_all = TRUE) %>%
# add the ones without WHONET code
bind_rows(
DRGLST %>%
select(ab = WHON5_CODE,
name = ANTIBIOTIC) %>%
filter(is.na(ab)) %>%
distinct(name, .keep_all = TRUE)
# add new ab code later
) %>%
arrange(name)
# add old ATC codes
ab_old <- AMR::antibiotics %>%
mutate(official = gsub("( and |, )", "/", official),
abbr = tolower(paste(ifelse(is.na(abbr), "", abbr),
ifelse(is.na(certe), "", certe),
ifelse(is.na(umcg), "", umcg),
sep = "|")))
for (i in 1:nrow(ab_old)) {
abbr <- ab_old[i, "abbr"]
abbr <- strsplit(abbr, "|", fixed = TRUE) %>% unlist() %>% unique()
abbr <- abbr[abbr != ""]
#print(abbr)
if (length(abbr) == 0) {
ab_old[i, "abbr"] <- NA_character_
} else {
ab_old[i, "abbr"] <- paste(abbr, collapse = "|")
}
}
# create reference data set: to be able to map ab to atc
abx_atc1 <- abx %>%
mutate(name_lower = tolower(name)) %>%
left_join(ab_old %>%
select(ears_net, atc), by = c(ab = "ears_net")) %>%
rename(atc1 = atc) %>%
left_join(ab_old %>%
mutate(official = gsub(", combinations", "", official, fixed = TRUE)) %>%
transmute(official = tolower(official), atc), by = c(name_lower = "official")) %>%
rename(atc2 = atc) %>%
left_join(ab_old %>%
mutate(official = gsub(", combinations", "", official, fixed = TRUE)) %>%
mutate(official = gsub("f", "ph", official)) %>%
transmute(official = tolower(official), atc), by = c(name_lower = "official")) %>%
rename(atc3 = atc) %>%
left_join(ab_old %>%
mutate(official = gsub(", combinations", "", official, fixed = TRUE)) %>%
mutate(official = gsub("t", "th", official)) %>%
transmute(official = tolower(official), atc), by = c(name_lower = "official")) %>%
rename(atc4 = atc) %>%
left_join(ab_old %>%
mutate(official = gsub(", combinations", "", official, fixed = TRUE)) %>%
mutate(official = gsub("f", "ph", official)) %>%
mutate(official = gsub("t", "th", official)) %>%
transmute(official = tolower(official), atc), by = c(name_lower = "official")) %>%
rename(atc5 = atc) %>%
left_join(ab_old %>%
mutate(official = gsub(", combinations", "", official, fixed = TRUE)) %>%
mutate(official = gsub("f", "ph", official)) %>%
mutate(official = gsub("t", "th", official)) %>%
mutate(official = gsub("ine$", "in", official)) %>%
transmute(official = tolower(official), atc), by = c(name_lower = "official")) %>%
rename(atc6 = atc) %>%
mutate(atc = case_when(!is.na(atc1) ~ atc1,
!is.na(atc2) ~ atc2,
!is.na(atc3) ~ atc3,
!is.na(atc4) ~ atc4,
!is.na(atc4) ~ atc5,
TRUE ~ atc6)) %>%
distinct(ab, name, .keep_all = TRUE) %>%
select(ab, atc, name)
abx_atc2 <- ab_old %>%
filter(!atc %in% abx_atc1$atc,
is.na(ears_net),
!is.na(atc_group1),
!atc_group1 %like% ("virus|vaccin|viral|immun"),
!official %like% "(combinations| with )") %>%
mutate(ab = NA_character_) %>%
as.data.frame(stringsAsFactors = FALSE) %>%
select(ab, atc, name = official)
abx2 <- bind_rows(abx_atc1, abx_atc2)
rm(abx_atc1)
rm(abx_atc2)
abx2$ab[is.na(abx2$ab)] <- toupper(abbreviate(gsub("[/0-9-]",
" ",
abx2$name[is.na(abx2$ab)]),
minlength = 3,
method = "left.kept",
strict = TRUE))
n_distinct(abx2$ab)
abx2 <- abx2 %>% arrange(ab)
seqnr <- 0
# add follow up nrs
for (i in 2:nrow(abx2)) {
if (abx2[i, "ab"] == abx2[i - 1, "ab"]) {
seqnr <- seqnr + 1
abx2[i, "seqnr"] <- seqnr
} else {
seqnr <- 0
}
}
for (i in 2:nrow(abx2)) {
if (!is.na(abx2[i, "seqnr"])) {
abx2[i, "ab"] <- paste0(abx2[i, "ab"], abx2[i, "seqnr"])
}
}
abx2 <- abx2 %>% select(-seqnr) %>% arrange(name)
# everything unique??
nrow(abx2) == n_distinct(abx2$ab)
# get ATC properties
abx2 <- abx2 %>%
left_join(ab_old %>%
select(atc, abbr, atc_group1, atc_group2,
oral_ddd, oral_units, iv_ddd, iv_units))
abx2$abbr <- lapply(as.list(abx2$abbr), function(x) unlist(strsplit(x, "|", fixed = TRUE)))
# vector with official names, returns vector with CIDs
get_CID <- function(ab) {
CID <- rep(NA_integer_, length(ab))
p <- progress_estimated(n = length(ab), min_time = 0)
for (i in 1:length(ab)) {
p$tick()$print()
CID[i] <- tryCatch(
data.table::fread(paste0("https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/",
URLencode(ab[i], reserved = TRUE),
"/cids/TXT?name_type=complete"),
showProgress = FALSE)[[1]][1],
error = function(e) NA_integer_)
if (is.na(CID[i])) {
# try with removing the text in brackets
CID[i] <- tryCatch(
data.table::fread(paste0("https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/",
URLencode(trimws(gsub("[(].*[)]", "", ab[i])), reserved = TRUE),
"/cids/TXT?name_type=complete"),
showProgress = FALSE)[[1]][1],
error = function(e) NA_integer_)
}
if (is.na(CID[i])) {
# try match on word and take the lowest CID value (sorted)
ab[i] <- gsub("[^a-z0-9]+", " ", ab[i], ignore.case = TRUE)
CID[i] <- tryCatch(
data.table::fread(paste0("https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/",
URLencode(ab[i], reserved = TRUE),
"/cids/TXT?name_type=word"),
showProgress = FALSE)[[1]][1],
error = function(e) NA_integer_)
}
Sys.sleep(0.1)
}
CID
}
# get CIDs (2-3 min)
CIDs <- get_CID(abx2$name)
# These could not be found:
abx2[is.na(CIDs),] %>% View()
# returns list with synonyms (brand names), with CIDs as names
get_synonyms <- function(CID, clean = TRUE) {
synonyms <- rep(NA_character_, length(CID))
p <- progress_estimated(n = length(CID), min_time = 0)
for (i in 1:length(CID)) {
p$tick()$print()
synonyms_txt <- ""
if (is.na(CID[i])) {
next
}
synonyms_txt <- tryCatch(
data.table::fread(paste0("https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/fastidentity/cid/",
CID[i],
"/synonyms/TXT"),
sep = "\n",
showProgress = FALSE)[[1]],
error = function(e) NA_character_)
Sys.sleep(0.1)
if (clean == TRUE) {
# remove text between brackets
synonyms_txt <- trimws(gsub("[(].*[)]", "",
gsub("[[].*[]]", "",
gsub("[(].*[]]", "",
gsub("[[].*[)]", "", synonyms_txt)))))
synonyms_txt <- gsub("Co-", "Co", synonyms_txt, fixed = TRUE)
# only length 6 to 20 and no txt with reading marks or numbers and must start with capital letter (= brand)
synonyms_txt <- synonyms_txt[nchar(synonyms_txt) %in% c(6:20)
& !grepl("[-&{},_0-9/]", synonyms_txt)
& grepl("^[A-Z]", synonyms_txt, ignore.case = FALSE)]
synonyms_txt <- unlist(strsplit(synonyms_txt, ";", fixed = TRUE))
}
synonyms_txt <- unique(trimws(synonyms_txt[tolower(synonyms_txt) %in% unique(tolower(synonyms_txt))]))
synonyms[i] <- list(sort(synonyms_txt))
}
names(synonyms) <- CID
synonyms
}
# get brand names from PubChem (2-3 min)
synonyms <- get_synonyms(CIDs)
synonyms <- lapply(synonyms,
function(x) {
if (length(x) == 0 | all(is.na(x))) {
""
} else {
x
}})
# add them to data set
antibiotics <- abx2 %>%
left_join(DRGLST %>%
select(ab = WHON5_CODE, CLASS, SUBCLASS) %>%
distinct(ab, .keep_all = TRUE), by = "ab") %>%
transmute(ab,
atc,
cid = CIDs,
# no capital after a slash: Ampicillin/Sulbactam -> Ampicillin/sulbactam
name = name %>%
gsub("([/-])([A-Z])", "\\1\\L\\2", ., perl = TRUE) %>%
gsub("edta", "EDTA", ., ignore.case = TRUE),
group = case_when(
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "am(ph|f)enicol" ~ "Amphenicols",
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "aminoglycoside" ~ "Aminoglycosides",
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "carbapenem" | name %like% "(imipenem|meropenem)" ~ "Carbapenems",
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "First-generation cephalosporin" ~ "Cephalosporins (1st gen.)",
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "Second-generation cephalosporin" ~ "Cephalosporins (2nd gen.)",
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "Third-generation cephalosporin" ~ "Cephalosporins (3rd gen.)",
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "Fourth-generation cephalosporin" ~ "Cephalosporins (4th gen.)",
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "(tuberculosis|mycobacter)" ~ "Antimycobacterials",
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "cephalosporin" ~ "Cephalosporins",
name %like% "^Ce" & is.na(atc_group1) & paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "beta-?lactam" ~ "Cephalosporins",
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "(beta-?lactam|penicillin)" ~ "Beta-lactams/penicillins",
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "quinolone" ~ "Quinolones",
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "glycopeptide" ~ "Glycopeptides",
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "macrolide" ~ "Macrolides/lincosamides",
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "tetracycline" ~ "Tetracyclines",
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "trimethoprim" ~ "Trimethoprims",
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "polymyxin" ~ "Polymyxins",
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "(fungal|mycot)" ~ "Antifungals/antimycotics",
TRUE ~ "Other antibacterials"
),
atc_group1, atc_group2,
abbreviations = unname(abbr),
synonyms = unname(synonyms),
oral_ddd, oral_units,
iv_ddd, iv_units) %>%
as.data.frame(stringsAsFactors = FALSE)
# some exceptions
antibiotics[which(antibiotics$ab == "DOX"), "abbreviations"][[1]] <- list(c("dox", "doxy"))
antibiotics[which(antibiotics$ab == "FLC"), "abbreviations"][[1]] <- list(c("clox"))
antibiotics[which(antibiotics$ab == "CEC"), "abbreviations"][[1]] <- list(c(antibiotics[which(antibiotics$ab == "CEC"), "abbreviations"][[1]], "CFC")) # cefaclor old WHONET4 code
antibiotics[which(antibiotics$ab == "AMX"), "synonyms"][[1]] <- list(sort(c(antibiotics[which(antibiotics$ab == "AMX"), "synonyms"][[1]], "Amoxy")))
# 'Polymixin B' (POL) and 'Polymyxin B' (PLB) both exist, so:
antibiotics[which(antibiotics$ab == "PLB"), "abbreviations"][[1]] <- list(c(antibiotics[which(antibiotics$ab == "PLB"), "abbreviations"][[1]], "POL", "Polymixin", "Polymixin B"))
antibiotics <- filter(antibiotics, ab != "POL")
# 'Latamoxef' (LTM) and 'Moxalactam (Latamoxef)' (MOX) both exist, so:
antibiotics[which(antibiotics$ab == "LTM"), "abbreviations"][[1]] <- list(c("MOX", "moxa"))
antibiotics <- filter(antibiotics, ab != "MOX")
# RFP and RFP1 (the J0 one) both mean 'rifapentine', although 'rifp' is not recognised, so:
antibiotics <- filter(antibiotics, ab != "RFP")
antibiotics[which(antibiotics$ab == "RFP1"), "ab"] <- "RFP"
antibiotics[which(antibiotics$ab == "RFP"), "abbreviations"][[1]] <- list(c("rifp"))
# Rifampicin is better known as a drug than Rifampin (Rifampin is still listed as a brand name), so:
antibiotics[which(antibiotics$ab == "RIF"), "name"] <- "Rifampicin"
# PME and PVM1 (the J0 one) both mean 'Pivmecillinam', so:
antibiotics <- filter(antibiotics, ab != "PME")
antibiotics[which(antibiotics$ab == "PVM1"), "ab"] <- "PME"
# Remove Sinecatechins
antibiotics <- filter(antibiotics, ab != "SNC")
# ESBL E-test codes:
antibiotics[which(antibiotics$ab == "CCV"), "abbreviations"][[1]] <- list(c("xtzl"))
antibiotics[which(antibiotics$ab == "CAZ"), "abbreviations"][[1]] <- list(c(antibiotics[which(antibiotics$ab == "CAZ"), "abbreviations"][[1]], "xtz", "cefta"))
antibiotics[which(antibiotics$ab == "CPC"), "abbreviations"][[1]] <- list(c("xpml"))
antibiotics[which(antibiotics$ab == "FEP"), "abbreviations"][[1]] <- list(c(antibiotics[which(antibiotics$ab == "FEP"), "abbreviations"][[1]], "xpm"))
antibiotics[which(antibiotics$ab == "CTC"), "abbreviations"][[1]] <- list(c("xctl"))
antibiotics[which(antibiotics$ab == "CTX"), "abbreviations"][[1]] <- list(c(antibiotics[which(antibiotics$ab == "CTX"), "abbreviations"][[1]], "xct"))
# High level Gentamcin and Streptomycin
antibiotics[which(antibiotics$ab == "GEH"), "abbreviations"][[1]] <- list(c("gehl", "gentamicin high", "genta high"))
antibiotics[which(antibiotics$ab == "STH"), "abbreviations"][[1]] <- list(c("sthl", "streptomycin high", "strepto high"))
# add imi and "imipenem/cilastatine" to imipenem
antibiotics[which(antibiotics$ab == "IPM"), "abbreviations"][[1]] <- list(c("imip", "imi", "imp"))
antibiotics[which(antibiotics$ab == "IPM"), "synonyms"][[1]] <- list(sort(c(antibiotics[which(antibiotics$ab == "IPM"), "synonyms"][[1]], "imipenem/cilastatin")))
# add synonyms of ones not found
antibiotics[which(antibiotics$ab == "TZP"), "synonyms"][[1]] <- list(sort(c(antibiotics[which(antibiotics$ab == "TZP"), "synonyms"][[1]], "Tazocel", "tazocillin", "Tazocin", "Zosyn")))
antibiotics[which(antibiotics$ab == "COL"), "synonyms"][[1]] <- list(sort(unique(c(antibiotics[which(antibiotics$ab == "COL"), "synonyms"][[1]], "Colisticin", "Polymyxin E", "Colimycin", "Coly-Mycin", "Totazina", "Colistimethate", "Promixin", "Colistimethate Sodium"))))
# remove incorrect synonyms from rifampicin (RIF) and add them to the combination rifampicin/isoniazid (RFI)
old_sym <- antibiotics[which(antibiotics$ab == "RIF"), "synonyms"][[1]]
old_sym <- old_sym[!old_sym %in% c("Rifinah", "Rimactazid")]
antibiotics[which(antibiotics$ab == "RIF"), "synonyms"][[1]] <- list(old_sym)
antibiotics[which(antibiotics$ab == "RFI"), "synonyms"][[1]] <- list(sort(c("Rifinah", "Rimactazid")))
# remove incorrect synonyms from sulfamethoxazole (SMX) and add them to the combination trimethoprim/sulfamethoxazole (SXT)
old_sym <- antibiotics[which(antibiotics$ab == "SMX"), "synonyms"][[1]]
old_sym <- old_sym[!old_sym %in% c("Cotrimoxazole", "Bactrimel")]
antibiotics[which(antibiotics$ab == "SMX"), "synonyms"][[1]] <- list(old_sym)
antibiotics[which(antibiotics$ab == "SXT"), "synonyms"][[1]] <- list(sort(unique(c(antibiotics[which(antibiotics$ab == "COL"), "synonyms"][[1]], "Cotrimoxazole", "Bactrimel", "Septra", "Bactrim", "Cotrimazole"))))
## new ATC codes
# ceftaroline
antibiotics[which(antibiotics$ab == "CPT"), "atc"] <- "J01DI02"
# faropenem
antibiotics[which(antibiotics$ab == "FAR"), "atc"] <- "J01DI03"
# ceftobiprole
antibiotics[which(antibiotics$ab == "BPR"), "atc"] <- "J01DI01"
# typo
antibiotics[which(antibiotics$ab == "RXT"), "name"] <- "Roxithromycin"
antibiotics[which(antibiotics$ab == "PEN"), "atc"] <- "J01CE01"
antibiotics <- antibiotics %>% arrange(name)
# set cephalosporins groups for the ones that could not be determined automatically:
antibiotics <- antibiotics %>%
mutate(group = case_when(
name == "Cefcapene" ~ "Cephalosporins (3rd gen.)",
name == "Cefcapene pivoxil" ~ "Cephalosporins (3rd gen.)",
name == "Cefditoren pivoxil" ~ "Cephalosporins (3rd gen.)",
name == "Cefepime/clavulanic acid" ~ "Cephalosporins (4th gen.)",
name == "Cefepime/tazobactam" ~ "Cephalosporins (4th gen.)",
name == "Cefetamet pivoxil" ~ "Cephalosporins (3rd gen.)",
name == "Cefetecol (Cefcatacol)" ~ "Cephalosporins (4th gen.)",
name == "Cefetrizole" ~ "Cephalosporins (unclassified gen.)",
name == "Cefoselis" ~ "Cephalosporins (4th gen.)",
name == "Cefotaxime/clavulanic acid" ~ "Cephalosporins (3rd gen.)",
name == "Cefotaxime/sulbactam" ~ "Cephalosporins (3rd gen.)",
name == "Cefotiam hexetil" ~ "Cephalosporins (3rd gen.)",
name == "Cefovecin" ~ "Cephalosporins (3rd gen.)",
name == "Cefozopran" ~ "Cephalosporins (4th gen.)",
name == "Cefpimizole" ~ "Cephalosporins (3rd gen.)",
name == "Cefpodoxime proxetil" ~ "Cephalosporins (3rd gen.)",
name == "Cefpodoxime/clavulanic acid" ~ "Cephalosporins (3rd gen.)",
name == "Cefquinome" ~ "Cephalosporins (4th gen.)",
name == "Cefsumide" ~ "Cephalosporins (unclassified gen.)",
name == "Ceftaroline" ~ "Cephalosporins (5th gen.)",
name == "Ceftaroline/avibactam" ~ "Cephalosporins (5th gen.)",
name == "Ceftazidime/avibactam" ~ "Cephalosporins (3rd gen.)",
name == "Cefteram" ~ "Cephalosporins (3rd gen.)",
name == "Cefteram pivoxil" ~ "Cephalosporins (3rd gen.)",
name == "Ceftiofur" ~ "Cephalosporins (3rd gen.)",
name == "Ceftizoxime alapivoxil" ~ "Cephalosporins (3rd gen.)",
name == "Ceftobiprole" ~ "Cephalosporins (5th gen.)",
name == "Ceftobiprole medocaril" ~ "Cephalosporins (5th gen.)",
name == "Ceftolozane/enzyme inhibitor" ~ "Cephalosporins (5th gen.)",
name == "Ceftolozane/tazobactam" ~ "Cephalosporins (5th gen.)",
name == "Cefuroxime axetil" ~ "Cephalosporins (2nd gen.)",
TRUE ~ group))
# set as data.frame again
antibiotics <- as.data.frame(antibiotics, stringsAsFactors = FALSE)
class(antibiotics$ab) <- "ab"
# REFER TO data-raw/loinc.R FOR ADDING LOINC CODES
dim(antibiotics) # for R/data.R
usethis::use_data(antibiotics, overwrite = TRUE)
rm(antibiotics)
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