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add confidence intervals (fixed #70), remove combine_IR
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@ -5,7 +5,7 @@
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\alias{format.bug_drug_combinations}
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\title{Determine Bug-Drug Combinations}
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\source{
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\strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition}, 2014, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.
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\strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 5th Edition}, 2022, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.
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}
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\usage{
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bug_drug_combinations(x, col_mo = NULL, FUN = mo_shortname, ...)
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@ -16,7 +16,6 @@ bug_drug_combinations(x, col_mo = NULL, FUN = mo_shortname, ...)
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language = get_AMR_locale(),
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minimum = 30,
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combine_SI = TRUE,
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combine_IR = FALSE,
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add_ab_group = TRUE,
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remove_intrinsic_resistant = FALSE,
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decimal.mark = getOption("OutDec"),
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@ -39,9 +38,7 @@ bug_drug_combinations(x, col_mo = NULL, FUN = mo_shortname, ...)
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\item{minimum}{the minimum allowed number of available (tested) isolates. Any isolate count lower than \code{minimum} will return \code{NA} with a warning. The default number of \code{30} isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see \emph{Source}.}
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\item{combine_SI}{a \link{logical} to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant). This used to be the argument \code{combine_IR}, but this now follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. Default is \code{TRUE}.}
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\item{combine_IR}{a \link{logical} to indicate whether values R and I should be summed}
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\item{combine_SI}{a \link{logical} to indicate whether values S and I should be summed, so resistance will be based on only R, defaults to \code{TRUE}}
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\item{add_ab_group}{a \link{logical} to indicate where the group of the antimicrobials must be included as a first column}
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@ -61,7 +58,7 @@ The function \code{\link[=bug_drug_combinations]{bug_drug_combinations()}} retur
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Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use \code{\link[=format]{format()}} on the result to prettify it to a publishable/printable format, see \emph{Examples}.
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}
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\details{
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The function \code{\link[=format]{format()}} calculates the resistance per bug-drug combination. Use \code{combine_IR = FALSE} (default) to test R vs. S+I and \code{combine_IR = TRUE} to test R+I vs. S.
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The function \code{\link[=format]{format()}} calculates the resistance per bug-drug combination. Use \code{combine_SI = TRUE} (default) to test R vs. S+I and \code{combine_SI = FALSE} to test R+I vs. S.
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}
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\examples{
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\donttest{
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@ -36,8 +36,7 @@ count_df(
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data,
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translate_ab = "name",
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language = get_AMR_locale(),
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combine_SI = TRUE,
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combine_IR = FALSE
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combine_SI = TRUE
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)
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}
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\arguments{
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@ -51,9 +50,7 @@ count_df(
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\item{language}{language of the returned text, defaults to system language (see \code{\link[=get_AMR_locale]{get_AMR_locale()}}) and can also be set with \code{getOption("AMR_locale")}. Use \code{language = NULL} or \code{language = ""} to prevent translation.}
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\item{combine_SI}{a \link{logical} to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant). This used to be the argument \code{combine_IR}, but this now follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. Default is \code{TRUE}.}
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\item{combine_IR}{a \link{logical} to indicate whether all values of I and R must be merged into one, so the output only consists of S vs. I+R (susceptible vs. non-susceptible). This is outdated, see argument \code{combine_SI}.}
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\item{combine_SI}{a \link{logical} to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant), defaults to \code{TRUE}}
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}
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\value{
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An \link{integer}
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@ -7,7 +7,7 @@
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\source{
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Methodology of this function is strictly based on:
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\itemize{
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\item \strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition}, 2014, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.
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\item \strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 5th Edition}, 2022, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.
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\item Hindler JF and Stelling J (2007). \strong{Analysis and Presentation of Cumulative Antibiograms: A New Consensus Guideline from the Clinical and Laboratory Standards Institute.} Clinical Infectious Diseases, 44(6), 867-873. \doi{10.1086/511864}
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}
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}
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@ -20,7 +20,6 @@ ggplot_rsi(
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limits = NULL,
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translate_ab = "name",
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combine_SI = TRUE,
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combine_IR = FALSE,
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minimum = 30,
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language = get_AMR_locale(),
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nrow = NULL,
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@ -45,7 +44,6 @@ geom_rsi(
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minimum = 30,
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language = get_AMR_locale(),
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combine_SI = TRUE,
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combine_IR = FALSE,
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...
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)
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@ -64,7 +62,6 @@ labels_rsi_count(
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minimum = 30,
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language = get_AMR_locale(),
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combine_SI = TRUE,
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combine_IR = FALSE,
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datalabels.size = 3,
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datalabels.colour = "grey15"
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)
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@ -86,9 +83,7 @@ labels_rsi_count(
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\item{translate_ab}{a column name of the \link{antibiotics} data set to translate the antibiotic abbreviations to, using \code{\link[=ab_property]{ab_property()}}}
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\item{combine_SI}{a \link{logical} to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant). This used to be the argument \code{combine_IR}, but this now follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. Default is \code{TRUE}.}
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\item{combine_IR}{a \link{logical} to indicate whether all values of I and R must be merged into one, so the output only consists of S vs. I+R (susceptible vs. non-susceptible). This is outdated, see argument \code{combine_SI}.}
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\item{combine_SI}{a \link{logical} to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant), defaults to \code{TRUE}}
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\item{minimum}{the minimum allowed number of available (tested) isolates. Any isolate count lower than \code{minimum} will return \code{NA} with a warning. The default number of \code{30} isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see \emph{Source}.}
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@ -5,6 +5,7 @@
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\alias{resistance}
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\alias{portion}
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\alias{susceptibility}
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\alias{rsi_confidence_interval}
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\alias{proportion_R}
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\alias{proportion_IR}
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\alias{proportion_I}
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@ -14,13 +15,23 @@
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\alias{rsi_df}
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\title{Calculate Microbial Resistance}
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\source{
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\strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition}, 2014, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.
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\strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 5th Edition}, 2022, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.
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}
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\usage{
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resistance(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)
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susceptibility(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)
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rsi_confidence_interval(
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...,
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ab_result = "R",
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minimum = 30,
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as_percent = FALSE,
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only_all_tested = FALSE,
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confidence_level = 0.95,
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side = "both"
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)
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proportion_R(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)
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proportion_IR(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)
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@ -38,7 +49,7 @@ proportion_df(
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minimum = 30,
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as_percent = FALSE,
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combine_SI = TRUE,
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combine_IR = FALSE
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confidence_level = 0.95
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)
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rsi_df(
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@ -48,7 +59,7 @@ rsi_df(
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minimum = 30,
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as_percent = FALSE,
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combine_SI = TRUE,
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combine_IR = FALSE
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confidence_level = 0.95
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)
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}
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\arguments{
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@ -60,15 +71,19 @@ rsi_df(
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\item{only_all_tested}{(for combination therapies, i.e. using more than one variable for \code{...}): a \link{logical} to indicate that isolates must be tested for all antibiotics, see section \emph{Combination Therapy} below}
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\item{ab_result}{antibiotic results to test against, must be one of more values of "R", "S", "I"}
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\item{confidence_level}{the confidence level for the returned confidence interval. For the calculation, the number of S or SI isolates, and R isolates are compared with the total number of available isolates with R, S, or I by using \code{\link[=binom.test]{binom.test()}}, i.e., the Clopper-Pearson method.}
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\item{side}{the side of the confidence interval to return. Defaults to \code{"both"} for a length 2 vector, but can also be (abbreviated as) \code{"min"}/\code{"left"}/\code{"lower"}/\code{"less"} or \code{"max"}/\code{"right"}/\code{"higher"}/\code{"greater"}.}
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\item{data}{a \link{data.frame} containing columns with class \code{\link{rsi}} (see \code{\link[=as.rsi]{as.rsi()}})}
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\item{translate_ab}{a column name of the \link{antibiotics} data set to translate the antibiotic abbreviations to, using \code{\link[=ab_property]{ab_property()}}}
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\item{language}{language of the returned text, defaults to system language (see \code{\link[=get_AMR_locale]{get_AMR_locale()}}) and can also be set with \code{getOption("AMR_locale")}. Use \code{language = NULL} or \code{language = ""} to prevent translation.}
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\item{combine_SI}{a \link{logical} to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant). This used to be the argument \code{combine_IR}, but this now follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. Default is \code{TRUE}.}
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\item{combine_IR}{a \link{logical} to indicate whether all values of I and R must be merged into one, so the output only consists of S vs. I+R (susceptible vs. non-susceptible). This is outdated, see argument \code{combine_SI}.}
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\item{combine_SI}{a \link{logical} to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant), defaults to \code{TRUE}}
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}
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\value{
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A \link{double} or, when \code{as_percent = TRUE}, a \link{character}.
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@ -81,6 +96,8 @@ These functions can be used to calculate the (co-)resistance or susceptibility o
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\details{
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The function \code{\link[=resistance]{resistance()}} is equal to the function \code{\link[=proportion_R]{proportion_R()}}. The function \code{\link[=susceptibility]{susceptibility()}} is equal to the function \code{\link[=proportion_SI]{proportion_SI()}}.
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Use \code{\link[=rsi_confidence_interval]{rsi_confidence_interval()}} to calculate the confidence interval, which relies on \code{\link[=binom.test]{binom.test()}}, i.e., the Clopper-Pearson method. This function returns a vector of length 2 at default for antimicrobial \emph{resistance}. Change the \code{side} argument to "left"/"min" or "right"/"max" to return a single value, and change the \code{ab_result} argument to e.g. \code{c("S", "I")} to test for antimicrobial \emph{susceptibility}, see Examples.
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\strong{Remember that you should filter your data to let it contain only first isolates!} This is needed to exclude duplicates and to reduce selection bias. Use \code{\link[=first_isolate]{first_isolate()}} to determine them in your data set.
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These functions are not meant to count isolates, but to calculate the proportion of resistance/susceptibility. Use the \code{\link[=count]{count()}} functions to count isolates. The function \code{\link[=susceptibility]{susceptibility()}} is essentially equal to \code{count_susceptible() / count_all()}. \emph{Low counts can influence the outcome - the \code{proportion} functions may camouflage this, since they only return the proportion (albeit being dependent on the \code{minimum} argument).}
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@ -144,8 +161,16 @@ This AMR package honours this (new) insight. Use \code{\link[=susceptibility]{su
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# run ?example_isolates for more info.
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# base R ------------------------------------------------------------
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resistance(example_isolates$AMX) # determines \%R
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susceptibility(example_isolates$AMX) # determines \%S+I
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# determines \%R
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resistance(example_isolates$AMX)
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rsi_confidence_interval(example_isolates$AMX)
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rsi_confidence_interval(example_isolates$AMX,
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confidence_level = 0.975)
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# determines \%S+I:
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susceptibility(example_isolates$AMX)
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rsi_confidence_interval(example_isolates$AMX,
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ab_result = c("S", "I"))
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# be more specific
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proportion_S(example_isolates$AMX)
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@ -157,12 +182,27 @@ proportion_R(example_isolates$AMX)
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# dplyr -------------------------------------------------------------
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\donttest{
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if (require("dplyr")) {
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example_isolates \%>\%
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group_by(ward) \%>\%
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summarise(
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r = resistance(CIP),
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n = n_rsi(CIP)
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) # n_rsi works like n_distinct in dplyr, see ?n_rsi
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}
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if (require("dplyr")) {
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example_isolates \%>\%
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group_by(ward) \%>\%
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summarise(
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cipro_R = resistance(CIP),
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ci_min = rsi_confidence_interval(CIP, side = "min"),
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ci_max = rsi_confidence_interval(CIP, side = "max"),
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)
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}
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if (require("dplyr")) {
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example_isolates \%>\%
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group_by(ward) \%>\%
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