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<h1>How to determine multi-drug resistance (MDR)</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">23 February 2020</h4>
<div class="hidden name"><code>MDR.Rmd</code></div>
</div>
<p>With the function <code><a href="../reference/mdro.html">mdro()</a></code>, you can determine which micro-organisms are multi-drug resistant organisms (MDRO).</p>
<div id="type-of-input" class="section level4">
<h4 class="hasAnchor">
<a href="#type-of-input" class="anchor"></a>Type of input</h4>
<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function takes a data set as input, such as a regular <code>data.frame</code>. It tries to automatically determine the right columns for info about your isolates, like the name of the species and all columns with results of antimicrobial agents. See the help page for more info about how to set the right settings for your data with the command <code><a href="../reference/mdro.html">?mdro</a></code>.</p>
<p>For WHONET data (and most other data), all settings are automatically set correctly.</p>
</div>
<div id="guidelines" class="section level4">
<h4 class="hasAnchor">
<a href="#guidelines" class="anchor"></a>Guidelines</h4>
<p>The function support multiple guidelines. You can select a guideline with the <code>guideline</code> parameter. Currently supported guidelines are (case-insensitive):</p>
<ul>
<li>
<p><code>guideline = "CMI2012"</code> (default)</p>
<p>Magiorakos AP, Srinivasan A <em>et al.</em> “Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance.” Clinical Microbiology and Infection (2012) (<a href="https://www.clinicalmicrobiologyandinfection.com/article/S1198-743X(14)61632-3/fulltext">link</a>)</p>
</li>
<li>
<p><code>guideline = "EUCAST"</code></p>
<p>The European international guideline - EUCAST Expert Rules Version 3.1 “Intrinsic Resistance and Exceptional Phenotypes Tables” (<a href="http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf">link</a>)</p>
</li>
<li>
<p><code>guideline = "TB"</code></p>
<p>The international guideline for multi-drug resistant tuberculosis - World Health Organization “Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis” (<a href="https://www.who.int/tb/publications/pmdt_companionhandbook/en/">link</a>)</p>
</li>
<li>
<p><code>guideline = "MRGN"</code></p>
<p>The German national guideline - Mueller et al. (2015) Antimicrobial Resistance and Infection Control 4:7. (<a href="https://doi.org/10.1186/s13756-015-0047-6">link</a>)</p>
</li>
<li>
<p><code>guideline = "BRMO"</code></p>
<p>The Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu “WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) [ZKH]” (<a href="https://www.rivm.nl/Documenten_en_publicaties/Professioneel_Praktisch/Richtlijnen/Infectieziekten/WIP_Richtlijnen/WIP_Richtlijnen/Ziekenhuizen/WIP_richtlijn_BRMO_Bijzonder_Resistente_Micro_Organismen_ZKH">link</a>)</p>
</li>
</ul>
</div>
<div id="examples" class="section level4">
<h4 class="hasAnchor">
<a href="#examples" class="anchor"></a>Examples</h4>
<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function always returns an ordered <code>factor</code>. For example, the output of the default guideline by Magiorakos <em>et al.</em> returns a <code>factor</code> with levels ‘Negative’, ‘MDR’, ‘XDR’ or ‘PDR’ in that order.</p>
<p>The next example uses the <code>example_isolates</code> data set. This is a data set included with this package and contains 2,000 microbial isolates with their full antibiograms. It reflects reality and can be used to practice AMR analysis. If we test the MDR/XDR/PDR guideline on this data set, we get:</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1"></a><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(dplyr) <span class="co"># to support pipes: %&gt;%</span></span></code></pre></div>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1"></a>example_isolates <span class="op">%&gt;%</span><span class="st"> </span></span>
<span id="cb2-2"><a href="#cb2-2"></a><span class="st"> </span><span class="kw"><a href="../reference/mdro.html">mdro</a></span>() <span class="op">%&gt;%</span><span class="st"> </span></span>
<span id="cb2-3"><a href="#cb2-3"></a><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>() <span class="co"># show frequency table of the result</span></span>
<span id="cb2-4"><a href="#cb2-4"></a><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `mo` as input for `col_mo`.</span></span>
<span id="cb2-5"><a href="#cb2-5"></a><span class="co"># </span><span class="al">NOTE</span><span class="co">: Auto-guessing columns suitable for analysis...OK.</span></span>
<span id="cb2-6"><a href="#cb2-6"></a><span class="co"># </span><span class="al">NOTE</span><span class="co">: Reliability will be improved if these antimicrobial results would be available too: SAM (ampicillin/sulbactam), ATM (aztreonam), CTT (cefotetan), CPT (ceftaroline), DAP (daptomycin), DOR (doripenem), ETP (ertapenem), FUS (fusidic acid), GEH (gentamicin-high), LVX (levofloxacin), MNO (minocycline), NET (netilmicin), PLB (polymyxin B), QDA (quinupristin/dalfopristin), STH (streptomycin-high), TLV (telavancin), TCC (ticarcillin/clavulanic acid)</span></span>
<span id="cb2-7"><a href="#cb2-7"></a><span class="co"># Warning in mdro(.): NA introduced for isolates where the available percentage of</span></span>
<span id="cb2-8"><a href="#cb2-8"></a><span class="co"># antimicrobial classes was below 50% (set with `pct_required_classes`)</span></span></code></pre></div>
<p><strong>Frequency table</strong></p>
<p>Class: factor &gt; ordered (numeric)<br>
Length: 2,000<br>
Levels: 4: Negative &lt; Multi-drug-resistant (MDR) &lt; Extensively drug-resistant …<br>
Available: 1,711 (85.55%, NA: 289 = 14.45%)<br>
Unique: 2</p>
<table class="table">
<thead><tr class="header">
<th align="left"></th>
<th align="left">Item</th>
<th align="right">Count</th>
<th align="right">Percent</th>
<th align="right">Cum. Count</th>
<th align="right">Cum. Percent</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="left">1</td>
<td align="left">Negative</td>
<td align="right">1596</td>
<td align="right">93.28%</td>
<td align="right">1596</td>
<td align="right">93.28%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Multi-drug-resistant (MDR)</td>
<td align="right">115</td>
<td align="right">6.72%</td>
<td align="right">1711</td>
<td align="right">100.00%</td>
</tr>
</tbody>
</table>
<p>For another example, I will create a data set to determine multi-drug resistant TB:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1"></a><span class="co"># a helper function to get a random vector with values S, I and R</span></span>
<span id="cb3-2"><a href="#cb3-2"></a><span class="co"># with the probabilities 50% - 10% - 40%</span></span>
<span id="cb3-3"><a href="#cb3-3"></a>sample_rsi &lt;-<span class="st"> </span><span class="cf">function</span>() {</span>
<span id="cb3-4"><a href="#cb3-4"></a> <span class="kw"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample</a></span>(<span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"S"</span>, <span class="st">"I"</span>, <span class="st">"R"</span>),</span>
<span id="cb3-5"><a href="#cb3-5"></a> <span class="dt">size =</span> <span class="dv">5000</span>,</span>
<span id="cb3-6"><a href="#cb3-6"></a> <span class="dt">prob =</span> <span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="fl">0.5</span>, <span class="fl">0.1</span>, <span class="fl">0.4</span>),</span>
<span id="cb3-7"><a href="#cb3-7"></a> <span class="dt">replace =</span> <span class="ot">TRUE</span>)</span>
<span id="cb3-8"><a href="#cb3-8"></a>}</span>
<span id="cb3-9"><a href="#cb3-9"></a></span>
<span id="cb3-10"><a href="#cb3-10"></a>my_TB_data &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span>(<span class="dt">rifampicin =</span> <span class="kw">sample_rsi</span>(),</span>
<span id="cb3-11"><a href="#cb3-11"></a> <span class="dt">isoniazid =</span> <span class="kw">sample_rsi</span>(),</span>
<span id="cb3-12"><a href="#cb3-12"></a> <span class="dt">gatifloxacin =</span> <span class="kw">sample_rsi</span>(),</span>
<span id="cb3-13"><a href="#cb3-13"></a> <span class="dt">ethambutol =</span> <span class="kw">sample_rsi</span>(),</span>
<span id="cb3-14"><a href="#cb3-14"></a> <span class="dt">pyrazinamide =</span> <span class="kw">sample_rsi</span>(),</span>
<span id="cb3-15"><a href="#cb3-15"></a> <span class="dt">moxifloxacin =</span> <span class="kw">sample_rsi</span>(),</span>
<span id="cb3-16"><a href="#cb3-16"></a> <span class="dt">kanamycin =</span> <span class="kw">sample_rsi</span>())</span></code></pre></div>
<p>Because all column names are automatically verified for valid drug names or codes, this would have worked exactly the same:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb4-1"><a href="#cb4-1"></a>my_TB_data &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span>(<span class="dt">RIF =</span> <span class="kw">sample_rsi</span>(),</span>
<span id="cb4-2"><a href="#cb4-2"></a> <span class="dt">INH =</span> <span class="kw">sample_rsi</span>(),</span>
<span id="cb4-3"><a href="#cb4-3"></a> <span class="dt">GAT =</span> <span class="kw">sample_rsi</span>(),</span>
<span id="cb4-4"><a href="#cb4-4"></a> <span class="dt">ETH =</span> <span class="kw">sample_rsi</span>(),</span>
<span id="cb4-5"><a href="#cb4-5"></a> <span class="dt">PZA =</span> <span class="kw">sample_rsi</span>(),</span>
<span id="cb4-6"><a href="#cb4-6"></a> <span class="dt">MFX =</span> <span class="kw">sample_rsi</span>(),</span>
<span id="cb4-7"><a href="#cb4-7"></a> <span class="dt">KAN =</span> <span class="kw">sample_rsi</span>())</span></code></pre></div>
<p>The data set now looks like this:</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb5-1"><a href="#cb5-1"></a><span class="kw"><a href="https://rdrr.io/r/utils/head.html">head</a></span>(my_TB_data)</span>
<span id="cb5-2"><a href="#cb5-2"></a><span class="co"># rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin</span></span>
<span id="cb5-3"><a href="#cb5-3"></a><span class="co"># 1 S R S R R I</span></span>
<span id="cb5-4"><a href="#cb5-4"></a><span class="co"># 2 S R S S R S</span></span>
<span id="cb5-5"><a href="#cb5-5"></a><span class="co"># 3 I S R R S R</span></span>
<span id="cb5-6"><a href="#cb5-6"></a><span class="co"># 4 S S S S S R</span></span>
<span id="cb5-7"><a href="#cb5-7"></a><span class="co"># 5 S S S I R R</span></span>
<span id="cb5-8"><a href="#cb5-8"></a><span class="co"># 6 I I R R S S</span></span>
<span id="cb5-9"><a href="#cb5-9"></a><span class="co"># kanamycin</span></span>
<span id="cb5-10"><a href="#cb5-10"></a><span class="co"># 1 S</span></span>
<span id="cb5-11"><a href="#cb5-11"></a><span class="co"># 2 I</span></span>
<span id="cb5-12"><a href="#cb5-12"></a><span class="co"># 3 R</span></span>
<span id="cb5-13"><a href="#cb5-13"></a><span class="co"># 4 R</span></span>
<span id="cb5-14"><a href="#cb5-14"></a><span class="co"># 5 R</span></span>
<span id="cb5-15"><a href="#cb5-15"></a><span class="co"># 6 I</span></span></code></pre></div>
<p>We can now add the interpretation of MDR-TB to our data set. You can use:</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb6-1"><a href="#cb6-1"></a><span class="kw"><a href="../reference/mdro.html">mdro</a></span>(my_TB_data, <span class="dt">guideline =</span> <span class="st">"TB"</span>)</span></code></pre></div>
<p>or its shortcut <code><a href="../reference/mdro.html">mdr_tb()</a></code>:</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb7-1"><a href="#cb7-1"></a>my_TB_data<span class="op">$</span>mdr &lt;-<span class="st"> </span><span class="kw"><a href="../reference/mdro.html">mdr_tb</a></span>(my_TB_data)</span>
<span id="cb7-2"><a href="#cb7-2"></a><span class="co"># </span><span class="al">NOTE</span><span class="co">: No column found as input for `col_mo`, assuming all records contain Mycobacterium tuberculosis.</span></span>
<span id="cb7-3"><a href="#cb7-3"></a><span class="co"># </span><span class="al">NOTE</span><span class="co">: Auto-guessing columns suitable for analysis...OK.</span></span>
<span id="cb7-4"><a href="#cb7-4"></a><span class="co"># </span><span class="al">NOTE</span><span class="co">: Reliability will be improved if these antimicrobial results would be available too: CAP (capreomycin), RIB (rifabutin), RFP (rifapentine)</span></span></code></pre></div>
<p>Create a frequency table of the results:</p>
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb8-1"><a href="#cb8-1"></a><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(my_TB_data<span class="op">$</span>mdr)</span></code></pre></div>
<p><strong>Frequency table</strong></p>
<p>Class: factor &gt; ordered (numeric)<br>
Length: 5,000<br>
Levels: 5: Negative &lt; Mono-resistant &lt; Poly-resistant &lt; Multi-drug-resistant &lt;<br>
Available: 5,000 (100%, NA: 0 = 0%)<br>
Unique: 5</p>
<table class="table">
<thead><tr class="header">
<th align="left"></th>
<th align="left">Item</th>
<th align="right">Count</th>
<th align="right">Percent</th>
<th align="right">Cum. Count</th>
<th align="right">Cum. Percent</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="left">1</td>
<td align="left">Mono-resistant</td>
<td align="right">3274</td>
<td align="right">65.48%</td>
<td align="right">3274</td>
<td align="right">65.48%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Negative</td>
<td align="right">651</td>
<td align="right">13.02%</td>
<td align="right">3925</td>
<td align="right">78.50%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Multi-drug-resistant</td>
<td align="right">612</td>
<td align="right">12.24%</td>
<td align="right">4537</td>
<td align="right">90.74%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Poly-resistant</td>
<td align="right">288</td>
<td align="right">5.76%</td>
<td align="right">4825</td>
<td align="right">96.50%</td>
</tr>
<tr class="odd">
<td align="left">5</td>
<td align="left">Extensively drug-resistant</td>
<td align="right">175</td>
<td align="right">3.50%</td>
<td align="right">5000</td>
<td align="right">100.00%</td>
</tr>
</tbody>
</table>
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