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<h1>How to determine multi-drug resistance (MDR)</h1>
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<h4 class="author">Matthijs S. Berends</h4>
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<h4 class="date">13 October 2019</h4>
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<div class="hidden name"><code>MDR.Rmd</code></div>
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<p>With the function <code><a href="../reference/mdro.html">mdro()</a></code>, you can determine multi-drug resistant organisms (MDRO). It currently support these guidelines:</p>
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<ul>
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<li>“Intrinsic Resistance and Exceptional Phenotypes Tables”, by EUCAST (European Committee on Antimicrobial Susceptibility Testing)</li>
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<li>“Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis”, by WHO (World Health Organization)</li>
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<li>“WIP-Richtlijn Bijzonder Resistente Micro-organismen (BRMO)”, by RIVM (Rijksinstituut voor de Volksgezondheid, the Netherlands National Institute for Public Health and the Environment)</li>
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<p>As an example, I will make a data set to determine multi-drug resistant TB:</p>
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<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="co"># a helper function to get a random vector with values S, I and R</span></a>
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<a class="sourceLine" id="cb1-2" data-line-number="2"><span class="co"># with the probabilities 50% - 10% - 40%</span></a>
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<a class="sourceLine" id="cb1-3" data-line-number="3">sample_rsi <-<span class="st"> </span><span class="cf">function</span>() {</a>
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<a class="sourceLine" id="cb1-4" data-line-number="4"> <span class="kw"><a href="https://rdrr.io/r/base/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>),</a>
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<a class="sourceLine" id="cb1-5" data-line-number="5"> <span class="dt">size =</span> <span class="dv">5000</span>,</a>
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<a class="sourceLine" id="cb1-6" data-line-number="6"> <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>),</a>
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<a class="sourceLine" id="cb1-7" data-line-number="7"> <span class="dt">replace =</span> <span class="ot">TRUE</span>)</a>
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<a class="sourceLine" id="cb1-8" data-line-number="8">}</a>
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<a class="sourceLine" id="cb1-9" data-line-number="9"></a>
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<a class="sourceLine" id="cb1-10" data-line-number="10">my_TB_data <-<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>(),</a>
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<a class="sourceLine" id="cb1-11" data-line-number="11"> <span class="dt">isoniazid =</span> <span class="kw">sample_rsi</span>(),</a>
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<a class="sourceLine" id="cb1-12" data-line-number="12"> <span class="dt">gatifloxacin =</span> <span class="kw">sample_rsi</span>(),</a>
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<a class="sourceLine" id="cb1-13" data-line-number="13"> <span class="dt">ethambutol =</span> <span class="kw">sample_rsi</span>(),</a>
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<a class="sourceLine" id="cb1-14" data-line-number="14"> <span class="dt">pyrazinamide =</span> <span class="kw">sample_rsi</span>(),</a>
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<a class="sourceLine" id="cb1-15" data-line-number="15"> <span class="dt">moxifloxacin =</span> <span class="kw">sample_rsi</span>(),</a>
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<a class="sourceLine" id="cb1-16" data-line-number="16"> <span class="dt">kanamycin =</span> <span class="kw">sample_rsi</span>())</a></code></pre></div>
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<p>Because all column names are automatically verified for valid drug names or codes, this would have worked exactly the same:</p>
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<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" data-line-number="1">my_TB_data <-<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>(),</a>
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<a class="sourceLine" id="cb2-2" data-line-number="2"> <span class="dt">INH =</span> <span class="kw">sample_rsi</span>(),</a>
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<a class="sourceLine" id="cb2-3" data-line-number="3"> <span class="dt">GAT =</span> <span class="kw">sample_rsi</span>(),</a>
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<a class="sourceLine" id="cb2-4" data-line-number="4"> <span class="dt">ETH =</span> <span class="kw">sample_rsi</span>(),</a>
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<a class="sourceLine" id="cb2-5" data-line-number="5"> <span class="dt">PZA =</span> <span class="kw">sample_rsi</span>(),</a>
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<a class="sourceLine" id="cb2-6" data-line-number="6"> <span class="dt">MFX =</span> <span class="kw">sample_rsi</span>(),</a>
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<a class="sourceLine" id="cb2-7" data-line-number="7"> <span class="dt">KAN =</span> <span class="kw">sample_rsi</span>())</a></code></pre></div>
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<p>The data set looks like this now:</p>
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<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/utils/head.html">head</a></span>(my_TB_data)</a>
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<a class="sourceLine" id="cb3-2" data-line-number="2"><span class="co"># rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin</span></a>
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<a class="sourceLine" id="cb3-3" data-line-number="3"><span class="co"># 1 R S S I S S</span></a>
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<a class="sourceLine" id="cb3-4" data-line-number="4"><span class="co"># 2 I R S R S R</span></a>
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<a class="sourceLine" id="cb3-5" data-line-number="5"><span class="co"># 3 S S R R R R</span></a>
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<a class="sourceLine" id="cb3-6" data-line-number="6"><span class="co"># 4 S R R S S S</span></a>
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<a class="sourceLine" id="cb3-7" data-line-number="7"><span class="co"># 5 S R R S R R</span></a>
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<a class="sourceLine" id="cb3-8" data-line-number="8"><span class="co"># 6 R S S R R S</span></a>
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<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co"># kanamycin</span></a>
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<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># 1 R</span></a>
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<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># 2 R</span></a>
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<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># 3 I</span></a>
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<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># 4 S</span></a>
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<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># 5 S</span></a>
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<a class="sourceLine" id="cb3-15" data-line-number="15"><span class="co"># 6 S</span></a></code></pre></div>
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<p>We can now add the interpretation of MDR-TB to our data set:</p>
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<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1">my_TB_data<span class="op">$</span>mdr <-<span class="st"> </span><span class="kw"><a href="../reference/mdro.html">mdr_tb</a></span>(my_TB_data)</a>
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<a class="sourceLine" id="cb4-2" data-line-number="2"><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></a>
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<a class="sourceLine" id="cb4-3" data-line-number="3"><span class="co"># Determining multidrug-resistant organisms (MDRO), according to:</span></a>
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<a class="sourceLine" id="cb4-4" data-line-number="4"><span class="co"># Guideline: Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis</span></a>
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<a class="sourceLine" id="cb4-5" data-line-number="5"><span class="co"># Version: WHO/HTM/TB/2014.11</span></a>
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<a class="sourceLine" id="cb4-6" data-line-number="6"><span class="co"># Author: WHO (World Health Organization)</span></a>
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<a class="sourceLine" id="cb4-7" data-line-number="7"><span class="co"># Source: https://www.who.int/tb/publications/pmdt_companionhandbook/en/</span></a>
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<a class="sourceLine" id="cb4-8" data-line-number="8"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Auto-guessing columns suitable for analysis...</span></a>
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<a class="sourceLine" id="cb4-9" data-line-number="9"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Reliability might be improved if these antimicrobial results would be available too: CAP (capreomycin), RIB (rifabutin), RFP (rifapentine)</span></a></code></pre></div>
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<p>We also created a package dedicated to data cleaning and checking, called the <code>clean</code> package. It gets automatically installed with the <code>AMR</code> package, so we only have to load it:</p>
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<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(clean)</a></code></pre></div>
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<p>It contains the <code><a href="https://rdrr.io/pkg/clean/man/freq.html">freq()</a></code> function, to create a frequency table:</p>
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<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/pkg/clean/man/freq.html">freq</a></span>(my_TB_data<span class="op">$</span>mdr)</a></code></pre></div>
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<p><strong>Frequency table</strong></p>
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<p>Class: factor > ordered (numeric)<br>
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Length: 5,000 (of which NA: 0 = 0%)<br>
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Levels: 5: Negative < Mono-resistant < Poly-resistant < Multi-drug-resistant <…<br>
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Unique: 5</p>
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<table class="table">
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<thead><tr class="header">
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<th align="left"></th>
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<th align="left">Item</th>
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<th align="right">Count</th>
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<th align="right">Percent</th>
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<th align="right">Cum. Count</th>
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<th align="right">Cum. Percent</th>
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</tr></thead>
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<tbody>
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<tr class="odd">
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<td align="left">1</td>
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<td align="left">Mono-resistant</td>
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<td align="right">3246</td>
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<td align="right">64.92%</td>
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<td align="right">3246</td>
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<td align="right">64.92%</td>
|
|
</tr>
|
|
<tr class="even">
|
|
<td align="left">2</td>
|
|
<td align="left">Negative</td>
|
|
<td align="right">681</td>
|
|
<td align="right">13.62%</td>
|
|
<td align="right">3927</td>
|
|
<td align="right">78.54%</td>
|
|
</tr>
|
|
<tr class="odd">
|
|
<td align="left">3</td>
|
|
<td align="left">Multi-drug-resistant</td>
|
|
<td align="right">593</td>
|
|
<td align="right">11.86%</td>
|
|
<td align="right">4520</td>
|
|
<td align="right">90.40%</td>
|
|
</tr>
|
|
<tr class="even">
|
|
<td align="left">4</td>
|
|
<td align="left">Poly-resistant</td>
|
|
<td align="right">276</td>
|
|
<td align="right">5.52%</td>
|
|
<td align="right">4796</td>
|
|
<td align="right">95.92%</td>
|
|
</tr>
|
|
<tr class="odd">
|
|
<td align="left">5</td>
|
|
<td align="left">Extensive drug-resistant</td>
|
|
<td align="right">204</td>
|
|
<td align="right">4.08%</td>
|
|
<td align="right">5000</td>
|
|
<td align="right">100.00%</td>
|
|
</tr>
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</tbody>
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</table>
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