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<meta property="og:description" content="These functions can be used to calculate the (co-)resistance of microbial isolates (i.e. percentage S, SI, I, IR or R). All functions support quasiquotation with pipes, can be used in dplyrs summarise and support grouped variables, see Examples.
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portion_R and portion_IR can be used to calculate resistance, portion_S and portion_SI can be used to calculate susceptibility." />
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<h1>Calculate resistance of isolates</h1>
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<div class="hidden name"><code>portion.Rd</code></div>
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</div>
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<div class="ref-description">
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<p>These functions can be used to calculate the (co-)resistance of microbial isolates (i.e. percentage S, SI, I, IR or R). All functions support quasiquotation with pipes, can be used in <code>dplyr</code>s <code><a href='http://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></code> and support grouped variables, see <em>Examples</em>.</p>
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<p><code>portion_R</code> and <code>portion_IR</code> can be used to calculate resistance, <code>portion_S</code> and <code>portion_SI</code> can be used to calculate susceptibility.<br /></p>
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</div>
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<pre class="usage"><span class='fu'>portion_R</span>(<span class='no'>...</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
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<span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
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<span class='fu'>portion_IR</span>(<span class='no'>...</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
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<span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
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<span class='fu'>portion_I</span>(<span class='no'>...</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
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<span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
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<span class='fu'>portion_SI</span>(<span class='no'>...</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
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<span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
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<span class='fu'>portion_S</span>(<span class='no'>...</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
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<span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
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<span class='fu'>portion_df</span>(<span class='no'>data</span>, <span class='kw'>translate_ab</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a></span>(<span class='st'>"get_antibiotic_names"</span>,
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<span class='st'>"official"</span>), <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>combine_IR</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
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<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
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<table class="ref-arguments">
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<colgroup><col class="name" /><col class="desc" /></colgroup>
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<tr>
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<th>...</th>
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<td><p>one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with <code><a href='as.rsi.html'>as.rsi</a></code> if needed. Use multiple columns to calculate (the lack of) co-resistance: the probability where one of two drugs have a resistant or susceptible result. See Examples.</p></td>
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</tr>
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<tr>
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<th>minimum</th>
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<td><p>the minimal amount of available isolates. Any number lower than <code>minimum</code> will return <code>NA</code> with a warning. The default number of <code>30</code> isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see Source.</p></td>
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</tr>
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<tr>
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<th>as_percent</th>
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<td><p>a logical to indicate whether the output must be returned as a hundred fold with % sign (a character). A value of <code>0.123456</code> will then be returned as <code>"12.3%"</code>.</p></td>
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</tr>
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<tr>
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<th>also_single_tested</th>
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<td><p>a logical to indicate whether (in combination therapies) also observations should be included where not all antibiotics were tested, but at least one of the tested antibiotics contains a target interpretation (e.g. S in case of <code>portion_S</code> and R in case of <code>portion_R</code>). <strong>This would lead to selection bias in almost all cases.</strong></p></td>
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</tr>
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<tr>
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<th>data</th>
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<td><p>a <code>data.frame</code> containing columns with class <code>rsi</code> (see <code><a href='as.rsi.html'>as.rsi</a></code>)</p></td>
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</tr>
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<tr>
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<th>translate_ab</th>
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<td><p>a column name of the <code><a href='antibiotics.html'>antibiotics</a></code> data set to translate the antibiotic abbreviations to, using <code><a href='abname.html'>abname</a></code>. This can be set with <code><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a>("get_antibiotic_names")</code>.</p></td>
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</tr>
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<tr>
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<th>combine_IR</th>
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<td><p>a logical to indicate whether all values of I and R must be merged into one, so the output only consists of S vs. IR (susceptible vs. non-susceptible)</p></td>
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</tr>
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</table>
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<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
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<p><strong>M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition</strong>, 2014, <em>Clinical and Laboratory Standards Institute (CLSI)</em>. <a href='https://clsi.org/standards/products/microbiology/documents/m39/'>https://clsi.org/standards/products/microbiology/documents/m39/</a>.</p>
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<p>Wickham H. <strong>Tidy Data.</strong> The Journal of Statistical Software, vol. 59, 2014. <a href='http://vita.had.co.nz/papers/tidy-data.html'>http://vita.had.co.nz/papers/tidy-data.html</a></p>
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<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
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<p>Double or, when <code>as_percent = TRUE</code>, a character.</p>
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<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
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<p><strong>Remember that you should filter your table to let it contain only first isolates!</strong> Use <code><a href='first_isolate.html'>first_isolate</a></code> to determine them in your data set.</p>
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<p>These functions are not meant to count isolates, but to calculate the portion of resistance/susceptibility. Use the <code><a href='count.html'>count</a></code> functions to count isolates. <em>Low counts can infuence the outcome - these <code>portion</code> functions may camouflage this, since they only return the portion albeit being dependent on the <code>minimum</code> parameter.</em></p>
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<p><code>portion_df</code> takes any variable from <code>data</code> that has an <code>"rsi"</code> class (created with <code><a href='as.rsi.html'>as.rsi</a></code>) and calculates the portions R, I and S. The resulting <em>tidy data</em> (see Source) <code>data.frame</code> will have three rows (S/I/R) and a column for each variable with class <code>"rsi"</code>.</p>
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<p>The old <code><a href='rsi.html'>rsi</a></code> function is still available for backwards compatibility but is deprecated.
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<br /><br />
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To calculate the probability (<em>p</em>) of susceptibility of one antibiotic, we use this formula:
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<div style="text-align: center"><img src='figures/mono_therapy.png' alt='' /></div>
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To calculate the probability (<em>p</em>) of susceptibility of more antibiotics (i.e. combination therapy), we need to check whether one of them has a susceptible result (as numerator) and count all cases where all antibiotics were tested (as denominator). <br />
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<br />
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For two antibiotics:
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<div style="text-align: center"><img src='figures/combi_therapy_2.png' alt='' /></div>
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<br />
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For three antibiotics:
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<div style="text-align: center"><img src='figures/combi_therapy_3.png' alt='' /></div>
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<br />
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And so on.</p>
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<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
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<div class='dont-index'><p><code><a href='count.html'>count</a>_*</code> to count resistant and susceptible isolates.</p></div>
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<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
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<pre class="examples"><div class='input'><span class='co'># septic_patients is a data set available in the AMR package. It is true, genuine data.</span>
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?<span class='no'>septic_patients</span></div><div class='output co'>#> <span class='message'>Rendering development documentation for 'septic_patients'</span></div><div class='input'>
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<span class='co'># Calculate resistance</span>
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<span class='fu'>portion_R</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)</div><div class='output co'>#> [1] 0.5827645</div><div class='input'><span class='fu'>portion_IR</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)</div><div class='output co'>#> [1] 0.5853242</div><div class='input'>
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<span class='co'># Or susceptibility</span>
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<span class='fu'>portion_S</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)</div><div class='output co'>#> [1] 0.4146758</div><div class='input'><span class='fu'>portion_SI</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)</div><div class='output co'>#> [1] 0.4172355</div><div class='input'>
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<span class='co'># Do the above with pipes:</span>
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<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
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<span class='no'>septic_patients</span> <span class='kw'>%>%</span> <span class='fu'>portion_R</span>(<span class='no'>amox</span>)</div><div class='output co'>#> [1] 0.5827645</div><div class='input'><span class='no'>septic_patients</span> <span class='kw'>%>%</span> <span class='fu'>portion_IR</span>(<span class='no'>amox</span>)</div><div class='output co'>#> [1] 0.5853242</div><div class='input'><span class='no'>septic_patients</span> <span class='kw'>%>%</span> <span class='fu'>portion_S</span>(<span class='no'>amox</span>)</div><div class='output co'>#> [1] 0.4146758</div><div class='input'><span class='no'>septic_patients</span> <span class='kw'>%>%</span> <span class='fu'>portion_SI</span>(<span class='no'>amox</span>)</div><div class='output co'>#> [1] 0.4172355</div><div class='input'>
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<span class='no'>septic_patients</span> <span class='kw'>%>%</span>
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<span class='fu'><a href='http://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%>%</span>
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<span class='fu'><a href='http://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(<span class='kw'>p</span> <span class='kw'>=</span> <span class='fu'>portion_S</span>(<span class='no'>cipr</span>),
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<span class='kw'>n</span> <span class='kw'>=</span> <span class='fu'><a href='count.html'>n_rsi</a></span>(<span class='no'>cipr</span>)) <span class='co'># n_rsi works like n_distinct in dplyr</span></div><div class='output co'>#> <span style='color: #949494;'># A tibble: 4 x 3</span><span>
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#> hospital_id p n
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#> </span><span style='color: #949494;font-style: italic;'><fct></span><span> </span><span style='color: #949494;font-style: italic;'><dbl></span><span> </span><span style='color: #949494;font-style: italic;'><int></span><span>
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#> </span><span style='color: #BCBCBC;'>1</span><span> A 0.860 207
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#> </span><span style='color: #BCBCBC;'>2</span><span> B 0.760 499
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#> </span><span style='color: #BCBCBC;'>3</span><span> C 0.688 202
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#> </span><span style='color: #BCBCBC;'>4</span><span> D 0.830 501</div><div class='input'>
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<span class='no'>septic_patients</span> <span class='kw'>%>%</span>
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<span class='fu'><a href='http://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%>%</span>
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<span class='fu'><a href='http://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(<span class='kw'>R</span> <span class='kw'>=</span> <span class='fu'>portion_R</span>(<span class='no'>cipr</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
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<span class='kw'>I</span> <span class='kw'>=</span> <span class='fu'>portion_I</span>(<span class='no'>cipr</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
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<span class='kw'>S</span> <span class='kw'>=</span> <span class='fu'>portion_S</span>(<span class='no'>cipr</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
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<span class='kw'>n</span> <span class='kw'>=</span> <span class='fu'><a href='count.html'>n_rsi</a></span>(<span class='no'>cipr</span>), <span class='co'># works like n_distinct in dplyr</span>
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<span class='kw'>total</span> <span class='kw'>=</span> <span class='fu'><a href='http://dplyr.tidyverse.org/reference/n.html'>n</a></span>()) <span class='co'># NOT the amount of tested isolates!</span></div><div class='output co'>#> </span><span style='color: #949494;'># A tibble: 4 x 6</span><span>
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#> hospital_id R I S n total
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#> </span><span style='color: #949494;font-style: italic;'><fct></span><span> </span><span style='color: #949494;font-style: italic;'><chr></span><span> </span><span style='color: #949494;font-style: italic;'><chr></span><span> </span><span style='color: #949494;font-style: italic;'><chr></span><span> </span><span style='color: #949494;font-style: italic;'><int></span><span> </span><span style='color: #949494;font-style: italic;'><int></span><span>
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#> </span><span style='color: #BCBCBC;'>1</span><span> A 12.6% 1.4% 86.0% 207 321
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#> </span><span style='color: #BCBCBC;'>2</span><span> B 17.0% 7.0% 76.0% 499 663
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#> </span><span style='color: #BCBCBC;'>3</span><span> C 20.3% 10.9% 68.8% 202 254
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#> </span><span style='color: #BCBCBC;'>4</span><span> D 15.2% 1.8% 83.0% 501 762</div><div class='input'>
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<span class='co'># Calculate co-resistance between amoxicillin/clav acid and gentamicin,</span>
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<span class='co'># so we can see that combination therapy does a lot more than mono therapy:</span>
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<span class='no'>septic_patients</span> <span class='kw'>%>%</span> <span class='fu'>portion_S</span>(<span class='no'>amcl</span>) <span class='co'># S = 67.1%</span></div><div class='output co'>#> [1] 0.7062363</div><div class='input'><span class='no'>septic_patients</span> <span class='kw'>%>%</span> <span class='fu'><a href='count.html'>count_all</a></span>(<span class='no'>amcl</span>) <span class='co'># n = 1576</span></div><div class='output co'>#> [1] 1828</div><div class='input'>
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<span class='no'>septic_patients</span> <span class='kw'>%>%</span> <span class='fu'>portion_S</span>(<span class='no'>gent</span>) <span class='co'># S = 74.0%</span></div><div class='output co'>#> [1] 0.7396226</div><div class='input'><span class='no'>septic_patients</span> <span class='kw'>%>%</span> <span class='fu'><a href='count.html'>count_all</a></span>(<span class='no'>gent</span>) <span class='co'># n = 1855</span></div><div class='output co'>#> [1] 1855</div><div class='input'>
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<span class='no'>septic_patients</span> <span class='kw'>%>%</span> <span class='fu'>portion_S</span>(<span class='no'>amcl</span>, <span class='no'>gent</span>) <span class='co'># S = 92.0%</span></div><div class='output co'>#> [1] 0.9210074</div><div class='input'><span class='no'>septic_patients</span> <span class='kw'>%>%</span> <span class='fu'><a href='count.html'>count_all</a></span>(<span class='no'>amcl</span>, <span class='no'>gent</span>) <span class='co'># n = 1517</span></div><div class='output co'>#> [1] 1747</div><div class='input'>
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<span class='no'>septic_patients</span> <span class='kw'>%>%</span>
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<span class='fu'><a href='http://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%>%</span>
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<span class='fu'><a href='http://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(<span class='kw'>cipro_p</span> <span class='kw'>=</span> <span class='fu'>portion_S</span>(<span class='no'>cipr</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
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<span class='kw'>cipro_n</span> <span class='kw'>=</span> <span class='fu'><a href='count.html'>count_all</a></span>(<span class='no'>cipr</span>),
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<span class='kw'>genta_p</span> <span class='kw'>=</span> <span class='fu'>portion_S</span>(<span class='no'>gent</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
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<span class='kw'>genta_n</span> <span class='kw'>=</span> <span class='fu'><a href='count.html'>count_all</a></span>(<span class='no'>gent</span>),
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<span class='kw'>combination_p</span> <span class='kw'>=</span> <span class='fu'>portion_S</span>(<span class='no'>cipr</span>, <span class='no'>gent</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
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<span class='kw'>combination_n</span> <span class='kw'>=</span> <span class='fu'><a href='count.html'>count_all</a></span>(<span class='no'>cipr</span>, <span class='no'>gent</span>))</div><div class='output co'>#> </span><span style='color: #949494;'># A tibble: 4 x 7</span><span>
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#> hospital_id cipro_p cipro_n genta_p genta_n combination_p combination_n
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#> </span><span style='color: #949494;font-style: italic;'><fct></span><span> </span><span style='color: #949494;font-style: italic;'><chr></span><span> </span><span style='color: #949494;font-style: italic;'><int></span><span> </span><span style='color: #949494;font-style: italic;'><chr></span><span> </span><span style='color: #949494;font-style: italic;'><int></span><span> </span><span style='color: #949494;font-style: italic;'><chr></span><span> </span><span style='color: #949494;font-style: italic;'><int></span><span>
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#> </span><span style='color: #BCBCBC;'>1</span><span> A 86.0% 207 76.0% 300 95.0% 202
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#> </span><span style='color: #BCBCBC;'>2</span><span> B 76.0% 499 71.5% 606 91.4% 488
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#> </span><span style='color: #BCBCBC;'>3</span><span> C 68.8% 202 75.8% 240 91.5% 201
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#> </span><span style='color: #BCBCBC;'>4</span><span> D 83.0% 501 74.6% 709 95.0% 499</div><div class='input'>
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<span class='co'># Get portions S/I/R immediately of all rsi columns</span>
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<span class='no'>septic_patients</span> <span class='kw'>%>%</span>
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<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>amox</span>, <span class='no'>cipr</span>) <span class='kw'>%>%</span>
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<span class='fu'>portion_df</span>(<span class='kw'>translate</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</div><div class='output co'>#> Interpretation Antibiotic Value
|
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#> 1 S amox 0.414675768
|
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#> 2 I amox 0.002559727
|
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#> 3 R amox 0.582764505
|
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#> 4 S cipr 0.789212207
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#> 5 I cipr 0.048970901
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#> 6 R cipr 0.161816891</div><div class='input'>
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<span class='co'># It also supports grouping variables</span>
|
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<span class='no'>septic_patients</span> <span class='kw'>%>%</span>
|
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<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>hospital_id</span>, <span class='no'>amox</span>, <span class='no'>cipr</span>) <span class='kw'>%>%</span>
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<span class='fu'><a href='http://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%>%</span>
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<span class='fu'>portion_df</span>(<span class='kw'>translate</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</div><div class='output co'>#> </span><span style='color: #949494;'># A tibble: 24 x 4</span><span>
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#> Interpretation hospital_id Antibiotic Value
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#> </span><span style='color: #949494;font-style: italic;'><ord></span><span> </span><span style='color: #949494;font-style: italic;'><fct></span><span> </span><span style='color: #949494;font-style: italic;'><chr></span><span> </span><span style='color: #949494;font-style: italic;'><dbl></span><span>
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#> </span><span style='color: #BCBCBC;'> 1</span><span> S A amox 0.42
|
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#> </span><span style='color: #BCBCBC;'> 2</span><span> S B amox 0.378
|
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#> </span><span style='color: #BCBCBC;'> 3</span><span> S C amox 0.373
|
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#> </span><span style='color: #BCBCBC;'> 4</span><span> S D amox 0.454
|
|
#> </span><span style='color: #BCBCBC;'> 5</span><span> I A amox 0
|
|
#> </span><span style='color: #BCBCBC;'> 6</span><span> I B amox 0.002</span><span style='text-decoration: underline;'>68</span><span>
|
|
#> </span><span style='color: #BCBCBC;'> 7</span><span> I C amox 0
|
|
#> </span><span style='color: #BCBCBC;'> 8</span><span> I D amox 0.004</span><span style='text-decoration: underline;'>07</span><span>
|
|
#> </span><span style='color: #BCBCBC;'> 9</span><span> R A amox 0.580
|
|
#> </span><span style='color: #BCBCBC;'>10</span><span> R B amox 0.619
|
|
#> </span><span style='color: #949494;'># ... with 14 more rows</span><span></div><div class='input'>
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</div></span><span class='co'># NOT RUN {</span>
|
|
<span class='co'># calculate current empiric combination therapy of Helicobacter gastritis:</span>
|
|
<span class='no'>my_table</span> <span class='kw'>%>%</span>
|
|
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>first_isolate</span> <span class='kw'>==</span> <span class='fl'>TRUE</span>,
|
|
<span class='no'>genus</span> <span class='kw'>==</span> <span class='st'>"Helicobacter"</span>) <span class='kw'>%>%</span>
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<span class='fu'><a href='http://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(<span class='kw'>p</span> <span class='kw'>=</span> <span class='fu'>portion_S</span>(<span class='no'>amox</span>, <span class='no'>metr</span>), <span class='co'># amoxicillin with metronidazole</span>
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<span class='kw'>n</span> <span class='kw'>=</span> <span class='fu'><a href='count.html'>count_all</a></span>(<span class='no'>amox</span>, <span class='no'>metr</span>))
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<span class='co'># }</span></pre>
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</div>
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<div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
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<h2>Contents</h2>
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<ul class="nav nav-pills nav-stacked">
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<li><a href="#arguments">Arguments</a></li>
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<li><a href="#source">Source</a></li>
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<li><a href="#value">Value</a></li>
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<li><a href="#details">Details</a></li>
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<li><a href="#see-also">See also</a></li>
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<li><a href="#examples">Examples</a></li>
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</ul>
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</div>
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</div>
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<footer>
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<div class="copyright">
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<p>Developed by Matthijs S. Berends, Christian F. Luz.</p>
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</div>
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<div class="pkgdown">
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<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.3.0.</p>
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