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AMR/tests/testthat/test-mdro.R
Matthijs Berends 9af726dcaa mdro(): infer base drug resistance from drug+inhibitor combination co… (#263) 
* mdro(): infer base drug resistance from drug+inhibitor combination columns (#209)

When a base beta-lactam column (e.g., piperacillin/PIP) is absent but a
corresponding drug+inhibitor combination (e.g., piperacillin/tazobactam/TZP)
is present and resistant, resistance in the base drug is now correctly
inferred. This is clinically sound: resistance in a combination implies the
inhibitor provided no benefit, so the base drug is also resistant.

Susceptibility in a combination is NOT propagated to the base drug (the
inhibitor may be responsible for susceptibility), so only R values are
inferred; missing base drugs remain NA otherwise.

Implementation details:
- Uses AB_BETALACTAMS_WITH_INHIBITOR to identify all beta-lactam+inhibitor
  combinations present in the user's data
- Derives base drug AB codes by stripping the "/inhibitor" part from names
- Creates synthetic proxy columns (.sir_proxy_<AB>) in x, set to "R" when
  any matching combination is R, otherwise NA
- Proxy columns are added to cols_ab before drug variable assignment,
  so all existing guideline logic benefits without any changes
- Multiple combos for the same base drug are OR-ed (any R → R)
- Adds internal ab_without_inhibitor() helper for the name->base mapping
- Verbose mode reports which combinations are used for inference

Bumps version: 3.0.1.9028 -> 3.0.1.9029

https://claude.ai/code/session_01Cp154UtssHg84bw38xiiTG

* Add sir.R/mic.R fixes and mdro() unit tests; bump to 3.0.1.9030

R/sir.R (line 571):
  Guard purely numeric strings (e.g. "1", "8") from the Unicode letter
  filter. Values matching the broad SIR regex but consisting only of digits
  must not be stripped; add `x %unlike% "^[0-9+]$"` predicate.

R/mic.R (lines 220-222):
  Preserve the letter 'e' during Unicode-letter removal so that MIC values
  in scientific notation (e.g. "1e-3", "2.5e-2") survive the cleaning step.
  - Line 220: [\\p{L}] → [^e\\P{L}]  (remove all letters except 'e')
  - Line 222: [^0-9.><= -]+ → [^0-9e.><= -]+  (allow 'e' in whitelist)

tests/testthat/test-mdro.R:
  New tests for the drug+inhibitor inference added in the previous commit
  (issue #209):
  - TZP=R with no PIP column → PIP inferred R → MDRO class elevated
  - TZP=S with no PIP column → proxy col is NA (not S) → class lower
  - verbose mode emits "Inferring resistance" message
  - AMC=R with no AMX column runs without error (Enterococcus faecium)

https://claude.ai/code/session_01Cp154UtssHg84bw38xiiTG

* Fix version to single bump (9029) and update CLAUDE.md versioning rules

CLAUDE.md: Rewrite the "Version and date bump" subsection to document that:
- Exactly ONE version bump is allowed per PR (PRs are squash-merged into one
  commit on the default branch, so one commit = one version increment)
- The correct version is computed from git history:
    currentversion="${currenttag}.$((commits_since_tag + 9001 + 1))"
  with the +1 accounting for the PR's own squash commit not yet on the
  default branch
- Fall back to incrementing DESCRIPTION's version by 1 if git describe fails
- The Date: field tracks the date of the *last* PR commit (updated each time)

DESCRIPTION / NEWS.md: Correct the version from 3.0.1.9030 back to 3.0.1.9029.
Two version bumps were made across two commits in this PR; since it will be
squash-merged as one commit only one bump is correct. Also update Date to
today (2026-03-07).

https://claude.ai/code/session_01Cp154UtssHg84bw38xiiTG

* Fix stats::setNames, test accessor bug, and version script verification

R/mdro.R:
  Qualify setNames() as stats::setNames() in the drug+inhibitor inference
  block to satisfy R CMD CHECK's global-function checks.

tests/testthat/test-mdro.R:
  mdro() with verbose=FALSE returns an atomic ordered factor, not a
  data.frame. Fix three test errors introduced in the previous commit:
  - Line 320: result_no_pip$MDRO -> result_no_pip (factor, no $ accessor)
  - Line 328: result_tzp_s$MDRO / result_no_pip$MDRO -> direct factor refs
  - Line 347: expect_inherits(..., "data.frame") -> c("factor","ordered")
  Also fix the comment on line 347 to match the actual return type.

Version: confirmed at 3.0.1.9029 (no further bump; one bump already made
this PR). git describe failed (no tags in dev environment) — fallback
applies. The +1 in CLAUDE.md's formula is correct for tagged repos:
currentcommit + 9001 + 1 = 27 + 9001 + 1 = 9029 ✓

https://claude.ai/code/session_01Cp154UtssHg84bw38xiiTG

* Fix unit tests: use mrgn guideline and expect_message() for proxy tests

Three failures corrected:

1. Classification tests (lines 321, 329): The EUCAST guideline for
   P. aeruginosa already has OR logic (PIP OR TZP), so TZP=R alone
   satisfies it regardless of whether the PIP proxy exists. Switch to
   guideline="mrgn": the MRGN 4MRGN criterion for P. aeruginosa
   requires PIP=R explicitly (lines 1488-1496 of mdro.R), with no TZP
   fallback. Without the proxy: PIP missing -> not 4MRGN -> level 1.
   With the proxy (TZP=R infers PIP=R): 4MRGN reached -> level 3.
   The TZP=S case leaves proxy=NA, so PIP is still absent effectively
   -> level 1, which is < level 3 as expected.

2. Verbose/message test (line 335): message_() routes through message()
   to stderr, not cat() to stdout. expect_output() only captures stdout
   so it always saw nothing. Fix: use expect_message() instead, and
   remove the inner suppressMessages() that was swallowing the message
   before expect_message() could capture it.

Also trim two stale lines left over from the old expect_output block.

https://claude.ai/code/session_01Cp154UtssHg84bw38xiiTG

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-03-07 18:06:55 +01:00

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# ==================================================================== #
# TITLE: #
# AMR: An R Package for Working with Antimicrobial Resistance Data #
# #
# SOURCE CODE: #
# https://github.com/msberends/AMR #
# #
# PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, et al. (2022). #
# AMR: An R Package for Working with Antimicrobial Resistance Data. #
# Journal of Statistical Software, 104(3), 1-31. #
# https://doi.org/10.18637/jss.v104.i03 #
# #
# Developed at the University of Groningen and the University Medical #
# Center Groningen in The Netherlands, in collaboration with many #
# colleagues from around the world, see our website. #
# #
# 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 the full manual and a complete tutorial about #
# how to conduct AMR data analysis: https://amr-for-r.org #
# ==================================================================== #
test_that("test-mdro.R", {
skip_on_cran()
expect_error(mdro(example_isolates, guideline = c("BRMO", "MRGN"), info = TRUE))
expect_error(mdro(example_isolates, col_mo = "invalid", info = TRUE))
expect_output(suppressMessages(suppressWarnings(mdro(example_isolates, info = TRUE))))
expect_output(suppressMessages(suppressWarnings(mdro(example_isolates, "eucast3.1", info = TRUE))))
expect_output(suppressMessages(suppressWarnings(mdro(example_isolates, "eucast3.2", info = TRUE))))
expect_output(suppressMessages(suppressWarnings(mdro(example_isolates, "eucast3.3", info = TRUE))))
expect_output(outcome <- suppressMessages(suppressWarnings(eucast_exceptional_phenotypes(example_isolates, info = TRUE))))
# check class
expect_identical(class(outcome), c("ordered", "factor"))
expect_output(outcome <- mdro(example_isolates, "nl", info = TRUE))
# check class
expect_identical(class(outcome), c("ordered", "factor"))
# example_isolates should have these finding using Dutch guidelines
expect_equal(
as.double(table(outcome)),
c(1977, 21, 2)
)
expect_equal(
brmo(example_isolates, info = FALSE),
mdro(example_isolates, guideline = "BRMO", info = FALSE)
)
# test Dutch P. aeruginosa MDRO
expect_equal(
as.character(mdro(
data.frame(
mo = as.mo("P. aeruginosa"),
cfta = "S",
cipr = "S",
mero = "S",
imip = "S",
gent = "S",
tobr = "S",
pita = "S"
),
guideline = "BRMO",
col_mo = "mo",
info = FALSE
)),
"Negative"
)
expect_equal(
as.character(mdro(
data.frame(
mo = as.mo("P. aeruginosa"),
cefta = "R",
cipr = "R",
mero = "R",
imip = "R",
gent = "R",
tobr = "R",
pita = "R"
),
guideline = "BRMO",
col_mo = "mo",
info = FALSE
)),
"Positive"
)
# German 3MRGN and 4MRGN
expect_equal(
as.character(mrgn(
data.frame(
mo = c(
"E. coli", "E. coli", "K. pneumoniae", "E. coli",
"A. baumannii", "A. baumannii", "A. baumannii",
"P. aeruginosa", "P. aeruginosa", "P. aeruginosa"
),
PIP = c(
"S", "R", "R", "S",
"S", "R", "R",
"S", "R", "R"
),
CTX = c(
"S", "R", "R", "S",
"R", "R", "R",
"R", "R", "R"
),
IPM = c(
"S", "R", "S", "R",
"R", "R", "S",
"S", "R", "R"
),
CIP = c(
"S", "R", "R", "S",
"R", "R", "R",
"R", "S", "R"
),
stringsAsFactors = FALSE
)
)),
c("Negative", "4MRGN", "3MRGN", "4MRGN", "4MRGN", "4MRGN", "3MRGN", "Negative", "3MRGN", "4MRGN")
)
# MDR TB
expect_equal(
# select only rifampicine, mo will be determined automatically (as M. tuberculosis),
# number of mono-resistant strains should be equal to number of rifampicine-resistant strains
as.double(table(mdr_tb(example_isolates[, "RIF", drop = FALSE])))[2],
count_R(example_isolates$RIF)
)
x <- data.frame(
rifampicin = random_sir(5000, prob_sir = c(0.4, 0.1, 0.5)),
inh = random_sir(5000, prob_sir = c(0.4, 0.1, 0.5)),
gatifloxacin = random_sir(5000, prob_sir = c(0.4, 0.1, 0.5)),
eth = random_sir(5000, prob_sir = c(0.4, 0.1, 0.5)),
pza = random_sir(5000, prob_sir = c(0.4, 0.1, 0.5)),
MFX = random_sir(5000, prob_sir = c(0.4, 0.1, 0.5)),
KAN = random_sir(5000, prob_sir = c(0.4, 0.1, 0.5))
)
expect_true(length(unique(mdr_tb(x))) > 2)
# check the guideline by Magiorakos et al. (2012), the default guideline
stau <- data.frame(
mo = c("S. aureus", "S. aureus", "S. aureus", "S. aureus"),
GEN = c("R", "R", "S", "R"),
RIF = c("S", "R", "S", "R"),
CPT = c("S", "R", "R", "R"),
OXA = c("S", "R", "R", "R"),
CIP = c("S", "S", "R", "R"),
MFX = c("S", "S", "R", "R"),
SXT = c("S", "S", "R", "R"),
FUS = c("S", "S", "R", "R"),
VAN = c("S", "S", "R", "R"),
TEC = c("S", "S", "R", "R"),
TLV = c("S", "S", "R", "R"),
TGC = c("S", "S", "R", "R"),
CLI = c("S", "S", "R", "R"),
DAP = c("S", "S", "R", "R"),
ERY = c("S", "S", "R", "R"),
LNZ = c("S", "S", "R", "R"),
CHL = c("S", "S", "R", "R"),
FOS = c("S", "S", "R", "R"),
QDA = c("S", "S", "R", "R"),
TCY = c("S", "S", "R", "R"),
DOX = c("S", "S", "R", "R"),
MNO = c("S", "S", "R", "R"),
stringsAsFactors = FALSE
)
expect_equal(as.integer(mdro(stau)), c(1:4))
expect_inherits(mdro(stau, verbose = TRUE), "data.frame")
ente <- data.frame(
mo = c("Enterococcus", "Enterococcus", "Enterococcus", "Enterococcus"),
GEH = c("R", "R", "S", "R"),
STH = c("S", "R", "S", "R"),
IPM = c("S", "R", "R", "R"),
MEM = c("S", "R", "R", "R"),
DOR = c("S", "S", "R", "R"),
CIP = c("S", "S", "R", "R"),
LVX = c("S", "S", "R", "R"),
MFX = c("S", "S", "R", "R"),
VAN = c("S", "S", "R", "R"),
TEC = c("S", "S", "R", "R"),
TGC = c("S", "S", "R", "R"),
DAP = c("S", "S", "R", "R"),
LNZ = c("S", "S", "R", "R"),
AMP = c("S", "S", "R", "R"),
QDA = c("S", "S", "R", "R"),
DOX = c("S", "S", "R", "R"),
MNO = c("S", "S", "R", "R"),
stringsAsFactors = FALSE
)
expect_equal(as.integer(mdro(ente)), c(1:4))
expect_inherits(mdro(ente, verbose = TRUE), "data.frame")
entero <- data.frame(
mo = c("E. coli", "E. coli", "E. coli", "E. coli"),
GEN = c("R", "R", "S", "R"), TOB = c("S", "R", "S", "R"),
AMK = c("S", "R", "R", "R"), NET = c("S", "R", "R", "R"),
CPT = c("S", "R", "R", "R"), TCC = c("S", "R", "R", "R"),
TZP = c("S", "S", "R", "R"), ETP = c("S", "S", "R", "R"),
IPM = c("S", "S", "R", "R"), MEM = c("S", "S", "R", "R"),
DOR = c("S", "S", "R", "R"), CZO = c("S", "S", "R", "R"),
CXM = c("S", "S", "R", "R"), CTX = c("S", "S", "R", "R"),
CAZ = c("S", "S", "R", "R"), FEP = c("S", "S", "R", "R"),
FOX = c("S", "S", "R", "R"), CTT = c("S", "S", "R", "R"),
CIP = c("S", "S", "R", "R"), SXT = c("S", "S", "R", "R"),
TGC = c("S", "S", "R", "R"), ATM = c("S", "S", "R", "R"),
AMP = c("S", "S", "R", "R"), AMC = c("S", "S", "R", "R"),
SAM = c("S", "S", "R", "R"), CHL = c("S", "S", "R", "R"),
FOS = c("S", "S", "R", "R"), COL = c("S", "S", "R", "R"),
TCY = c("S", "S", "R", "R"), DOX = c("S", "S", "R", "R"),
MNO = c("S", "S", "R", "R"),
stringsAsFactors = FALSE
)
expect_equal(as.integer(mdro(entero)), c(1:4))
expect_inherits(mdro(entero, verbose = TRUE), "data.frame")
pseud <- data.frame(
mo = c("P. aeruginosa", "P. aeruginosa", "P. aeruginosa", "P. aeruginosa"),
GEN = c("R", "R", "S", "R"), TOB = c("S", "S", "S", "R"),
AMK = c("S", "S", "R", "R"), NET = c("S", "S", "R", "R"),
IPM = c("S", "R", "R", "R"), MEM = c("S", "S", "R", "R"),
DOR = c("S", "S", "R", "R"), CAZ = c("S", "S", "R", "R"),
FEP = c("S", "R", "R", "R"), CIP = c("S", "S", "R", "R"),
LVX = c("S", "S", "R", "R"), TCC = c("S", "S", "R", "R"),
TZP = c("S", "S", "R", "R"), ATM = c("S", "S", "R", "R"),
FOS = c("S", "S", "R", "R"), COL = c("S", "S", "R", "R"),
PLB = c("S", "S", "R", "R"),
stringsAsFactors = FALSE
)
expect_equal(as.integer(mdro(pseud)), c(1:4))
expect_inherits(mdro(pseud, verbose = TRUE), "data.frame")
acin <- data.frame(
mo = c("A. baumannii", "A. baumannii", "A. baumannii", "A. baumannii"),
GEN = c("R", "R", "S", "R"), TOB = c("S", "R", "S", "R"),
AMK = c("S", "R", "R", "R"), NET = c("S", "R", "R", "R"),
IPM = c("S", "S", "R", "R"), MEM = c("S", "R", "R", "R"),
DOR = c("S", "S", "R", "R"), CIP = c("S", "S", "R", "R"),
LVX = c("S", "S", "R", "R"), TZP = c("S", "S", "R", "R"),
TCC = c("S", "S", "R", "R"), CTX = c("S", "S", "R", "R"),
CRO = c("S", "S", "R", "R"), CAZ = c("S", "S", "R", "R"),
FEP = c("S", "R", "R", "R"), SXT = c("S", "S", "R", "R"),
SAM = c("S", "S", "R", "R"), COL = c("S", "S", "R", "R"),
PLB = c("S", "S", "R", "R"), TCY = c("S", "S", "R", "R"),
DOX = c("S", "S", "R", "R"), MNO = c("S", "S", "R", "R"),
stringsAsFactors = FALSE
)
expect_equal(as.integer(mdro(acin)), c(1:4))
expect_inherits(mdro(acin, verbose = TRUE), "data.frame")
# custom rules
custom <- custom_mdro_guideline("CIP == 'R' & age > 60" ~ "Elderly Type A",
"ERY == 'R' & age > 60" ~ "Elderly Type B",
as_factor = TRUE
)
expect_output(print(custom))
expect_output(print(c(custom, custom)))
expect_output(print(as.list(custom, custom)))
expect_output(x <- mdro(example_isolates, guideline = custom, info = TRUE))
expect_equal(as.double(table(x)), c(1070, 198, 732))
expect_output(print(custom_mdro_guideline(AMX == "R" ~ "test", as_factor = FALSE)))
expect_error(custom_mdro_guideline())
expect_error(custom_mdro_guideline("test"))
expect_error(custom_mdro_guideline("test" ~ c(1:3)))
expect_error(custom_mdro_guideline("test" ~ A))
# expect_warning(mdro(example_isolates,
# # since `test` gives an error, it will be ignored with a warning
# guideline = custom_mdro_guideline(test ~ "A"),
# info = FALSE
# ))
expect_equal(
colnames(suppressWarnings(mdro(example_isolates[1:10, ], verbose = TRUE, info = FALSE))),
c("row_number", "microorganism", "MDRO", "reason", "all_nonsusceptible_columns", "guideline")
)
expect_equal(
colnames(suppressWarnings(mdro(example_isolates[1:10, ], verbose = TRUE, info = FALSE, guideline = custom_mdro_guideline(AMX == "R" ~ "Positive")))),
c("row_number", "microorganism", "MDRO", "reason", "all_nonsusceptible_columns", "guideline")
)
# print groups
if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0", also_load = TRUE)) {
expect_output(x <- mdro(example_isolates %>% group_by(ward), info = TRUE, pct_required_classes = 0))
expect_output(x <- mdro(example_isolates %>% group_by(ward), guideline = custom, info = TRUE))
}
# drug+inhibitor inference for missing base drug columns (issue #209) -------
# Resistance in drug+inhibitor implies resistance in the base drug.
# MRGN guideline is used because it explicitly requires PIP=R (not PIP OR TZP)
# for Pseudomonas aeruginosa 4MRGN, making the proxy effect directly testable.
pseud_no_pip <- data.frame(
mo = as.mo("Pseudomonas aeruginosa"),
TZP = as.sir("R"), # piperacillin/tazobactam; no PIP column
CAZ = as.sir("R"),
IPM = as.sir("R"),
MEM = as.sir("R"),
CIP = as.sir("R"),
stringsAsFactors = FALSE
)
# Inference message goes to message() / stderr, not stdout
# -> must use expect_message(), NOT expect_output()
expect_message(
suppressWarnings(mdro(pseud_no_pip, guideline = "mrgn", info = FALSE, verbose = TRUE)),
"Inferring resistance"
)
# With TZP=R, PIP is inferred R -> 4MRGN criteria met -> level 3 (> 1)
result_no_pip <- suppressMessages(suppressWarnings(
mdro(pseud_no_pip, guideline = "mrgn", info = FALSE)
))
expect_true(as.integer(result_no_pip) > 1L)
# Susceptibility in combo does NOT propagate: proxy = NA, not S
# -> 4MRGN criteria no longer met -> lower level than when TZP=R
pseud_tzp_s <- pseud_no_pip
pseud_tzp_s$TZP <- as.sir("S")
result_tzp_s <- suppressMessages(suppressWarnings(
mdro(pseud_tzp_s, guideline = "mrgn", info = FALSE)
))
expect_true(as.integer(result_tzp_s) < as.integer(result_no_pip))
# Multiple combos for the same base drug: AMX can come from AMC (amoxicillin/clavulanic acid)
ente_no_amx <- data.frame(
mo = as.mo("Enterococcus faecium"),
AMC = as.sir("R"), # amoxicillin/clavulanic acid; no AMX column
VAN = as.sir("R"),
TEC = as.sir("R"),
LNZ = as.sir("R"),
DAP = as.sir("R"),
stringsAsFactors = FALSE
)
# Should run without error and return an ordered factor; AMX inferred R from AMC
expect_inherits(suppressMessages(suppressWarnings(mdro(ente_no_amx, guideline = "EUCAST", info = FALSE))), c("factor", "ordered"))
})
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