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		<title>If odds are not odd, what about odds ratios?</title>
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					<description><![CDATA[<p>What are the odds of developing a brain tumor from long-term use of cell phones? This is an evolving area of research.  Some studies have found an association and others have not. But two recent meta-analyses suggest that the odds are about 33 to 44% greater due to long-term cell phone usage. Got your attention?&#8230;</p>
<p>The post <a href="https://www.kddanalytics.com/if-odds-are-not-odd-what-about-odds-ratios/">If odds are not odd, what about odds ratios?</a> appeared first on <a href="https://www.kddanalytics.com">KDD Analytics</a>.</p>
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										<content:encoded><![CDATA[<p>What are the <strong>odds of developing a brain tumor from long-term use of cell phones</strong>?</p>
<p>This is an evolving area of research.  Some studies have found an association and others have not.</p>
<p>But two recent <strong><em><a href="https://en.wikipedia.org/wiki/Meta-analysis" target="_blank" rel="noopener">meta-analyses</a></em></strong> suggest that the odds are about <strong>33 to 44%</strong> <strong>greater</strong> due to long-term cell phone usage.</p>
<p>Got your attention?</p>
<p>“But what does this do to my odds of developing a brain tumor?” you may ask.</p>
<p>Before we answer that, we need to explain how the meta-analyses derive this 33 to 44% figure.  Which introduces us to <strong><em>odds ratios</em></strong>.</p>
<h2>Case-control studies</h2>
<p>Studies of the association between cell phone usage and brain tumor are typically <strong><em>case-control</em></strong> studies.</p>
<p>Such studies are <em><strong>retrospective</strong></em>, as opposed to <em><strong>prospective</strong></em>.<a href="#_ftn1" name="_ftnref1">[1]</a> They combine a sample of patients (<strong><em>cases</em></strong>) already diagnosed with a brain tumor with a random sample of non-patients (<strong><em>controls</em></strong>) drawn from the general population. Study investigators match controls to each case based on key demographics such as sex, age, and region.</p>
<p>The studies then measure and test for the existence of an association between <strong><em>exposure</em></strong> (cell phone usage) and <strong><em>outcome</em></strong> (brain tumor).<a href="#_ftn2" name="_ftnref2">[2]</a></p>
<p>Typically, these case-control studies report their <strong>estimated effects</strong>, not in terms of odds, but in terms of <strong>odds ratios</strong>.</p>
<p>So, what is an odds ratio?</p>
<h2>Odds ratios</h2>
<p>An odds ratio is a <strong>measure of association strength.</strong> In this case, between cell phone usage and the diagnosis of a brain tumor.</p>
<p>As an example, we can use the results from one of the <strong><em>high-quality</em></strong> <strong><a href="https://pubmed.ncbi.nlm.nih.gov/16023098/" target="_blank" rel="noopener">studies</a></strong> used in the meta-analyses mentioned above to show how odds ratios are calculated.<a href="#_ftn3" name="_ftnref3">[3]</a></p>
<p>The data shown in the following table are from a case-control study conducted in Sweden between 2000 and 2003.<a href="#_ftn4" name="_ftnref4">[4]</a>  The data are for long term cell phone usage (&gt;= 10 years). The reference category is no cell phone usage.<a href="#_ftn5" name="_ftnref5">[5]</a></p>
<p><img data-recalc-dims="1" decoding="async" loading="lazy" class="alignnone size-full wp-image-2023 aligncenter" src="https://i0.wp.com/www.kddanalytics.com/wp-content/uploads/2021/04/Odds-ratios.png?resize=399%2C120&#038;ssl=1" alt="cell phones and brain tumors" width="399" height="120" srcset="https://i0.wp.com/www.kddanalytics.com/wp-content/uploads/2021/04/Odds-ratios.png?w=399&amp;ssl=1 399w, https://i0.wp.com/www.kddanalytics.com/wp-content/uploads/2021/04/Odds-ratios.png?resize=300%2C90&amp;ssl=1 300w" sizes="auto, (max-width: 399px) 100vw, 399px" /><br />
In an earlier <strong><a href="https://www.kddanalytics.com/odds-and-probability-two-sides-of-the-same-coin/">article</a></strong> we learned that the odds of an event occurring are the number of events divided by the number of non-events.</p>
<p>Thus, the <strong>odds of a long-term cell phone user in this sample being diagnosed with a brain tumor</strong> is (16 / 232) or 0.069; about 1 to 14.</p>
<p>The <strong>odds of a non-cell phone user being diagnosed with a brain tumor</strong> is (18 / 674) or 0.027; about 1 to 37.</p>
<p>The <strong>odds ratio is simply the ratio of the two odds</strong>:  (0.069 / 0.027) or 2.582.</p>
<p>So, the odds of a long-term cell phone user being diagnosed with a brain tumor are <strong>2.582 times greater compared to a non-cell phone user</strong>.</p>
<p>Alternatively, this can be stated in <strong>terms of a % difference</strong>. The odds of a long-term cell phone user being diagnosed with a brain tumor are <strong>158% greater compared to a non-cell phone user</strong> ((2.582 – 1) * 100).</p>
<p>That is a pretty large effect.<a href="#_ftn6" name="_ftnref6">[6]</a></p>
<h2>Meta-studies</h2>
<p><strong>Now this is just one study</strong>.  The two meta-studies alluded to above each combined the results of 7 different, high-quality studies.</p>
<p>They found that the overall odds (across the studies) of a long-term cell phone user (&gt;= 10 years) being diagnosed with a brain tumor (any tumor type) are <a href="https://pubmed.ncbi.nlm.nih.gov/28213724/" target="_blank" rel="noopener"><strong>33%</strong></a> and (with respect to <a href="https://www.mayoclinic.org/diseases-conditions/glioma/symptoms-causes/syc-20350251" target="_blank" rel="noopener"><strong>glioma</strong></a>, a common type of tumor) <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5417432/" target="_blank" rel="noopener"><strong>44%</strong></a> <strong>greater compared to a non-cell phone user</strong>.<a href="#_ftn7" name="_ftnref7">[7]</a></p>
<p>These meta-studies found no effect due to cell phone usage over a shorter period (i.e., &lt; 10 years).</p>
<p>So, it appears that the risk, if it exists, is associated with long-term usage.  Moreover, using a cell phone on the same side of the head is associated with <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5417432/" target="_blank" rel="noopener"><strong>46%</strong></a> greater odds of developing a glioma on that side of the head.<a href="#_ftn8" name="_ftnref8">[8]</a></p>
<h2>Odds of developing a brain tumor</h2>
<p>So, <strong>back to our original question</strong>.  What are the odds of developing a brain tumor from long term cell phone usage?</p>
<p>The odds of developing a brain tumor among the general population is very low to start with.  Annual <strong><a href="https://seer.cancer.gov/statfacts/html/brain.html" target="_blank" rel="noopener">incidence</a></strong> in the US (2018) is 6.5 per 100,00 or 0.0065%.  In terms of odds, this is about 1 to 15,000.</p>
<p>So, a 44% increase in the odds would mean 9.4 per 100,000 or about 1 to 10,000.  Still quite low.<a href="#_ftn9" name="_ftnref9">[9]</a></p>
<p>As one <a href="https://academic.oup.com/jnci/article/103/15/1146/2516666" target="_blank" rel="noopener"><strong>researcher</strong></a> put it, “Your chance of being hurt by distracted driving because you’re using your cell phone wipes out the risk of getting cancer.”</p>
<p>However, in 2011 the World Health Organization’s International Agency for Research on Cancer (<a href="https://iarc.who.int/" target="_blank" rel="noopener"><strong>IARC</strong></a>) <strong><u>did</u> classify</strong> cell phones as a Group 2B <strong>carcinogen</strong> (i.e., possibly causes cancer).</p>
<p>And there continues to be a healthy debate in both the statistical and public arenas.</p>
<p><a href="https://ehtrust.org/scientific-documentation-cell-phone-radiation-associated-brain-tumor-rates-rising/" target="_blank" rel="noopener"><strong>Studies</strong></a> are continuing to be released which purportedly finding evidence that recent increasing rates in <a href="https://en.wikipedia.org/wiki/Glioblastoma" target="_blank" rel="noopener"><strong>glioblastomas</strong></a>, an aggressive type of cancer, are tied to cell phone usage.</p>
<p><a href="https://www.forbes.com/sites/geoffreykabat/2017/12/23/are-brain-cancer-rates-increasing-and-do-changes-relate-to-cell-phone-use/" target="_blank" rel="noopener"><strong>Skeptics</strong></a> argue that changes in WHO classification of what is considered a glioblastoma may be responsible for any uptick in brain tumor incidence. And that the large, increased risk reported by studies, like the meta-studies discussed above, are <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4057143/" target="_blank" rel="noopener"><strong>inconsistent</strong></a> with the historical trend in brain tumor incidence.<a href="#_ftn10" name="_ftnref10">[10]</a></p>
<p><strong>As we said at the outset, this is an evolving area of research, with lots of issues to untangle.</strong></p>
<p>One thing to keep in mind, though, is <strong>who is funding the research</strong>.  A topic we will cover in a later article.</p>
<h2>We have odds ratios to thank</h2>
<p><strong>Back to the main point of this article.</strong></p>
<p>Odds facilitate the measurement of the <strong><span style="text-decoration: underline;">relative</span> likelihood of events</strong>.  Epidemiological studies that are retrospective, commonly use the <strong>odds ratio as this relative measurement of association strength</strong>.</p>
<p>So, the next time you hear that your favorite dietary choice increases your chances of developing cancer, it is probably the result of that not-so-oddity, the odds ratio.</p>
<p>&nbsp;</p>
<p><a href="#_ftnref1" name="_ftn1">[1]</a> Prospective cohort studies have also been used (i.e., studies which track subjects over time).  See <strong><a href="https://www.cognibrain.com/retrospective-vs-prospective-study-advantages-types-and-differences/" target="_blank" rel="noopener">here</a></strong> for a summary of the advantages and disadvantages of retrospective and prospective studies.</p>
<p><a href="#_ftnref2" name="_ftn2">[2]</a> Exposure is determined by answers to a lengthy questionnaire. Hence, one of the criticisms levied against case-control studies is respondent <strong><a href="https://catalogofbias.org/biases/recall-bias/" target="_blank" rel="noopener">recall bias</a></strong>. That is, whether respondents accurately recall their cell phone usage, particularly over a long period of time.</p>
<p><a href="#_ftnref3" name="_ftn3">[3]</a> Studies are <a href="http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp" target="_blank" rel="noopener"><strong>graded</strong></a> on a quality scale considering such factors as <strong>selection</strong> of cases and controls, <strong>comparability</strong> of cases and controls based on study design, and proper assessment/measurement of <strong>exposure</strong>.</p>
<p><a href="#_ftnref4" name="_ftn4">[4]</a> The results shown in the table are taken from a <a href="https://pubmed.ncbi.nlm.nih.gov/28213724/" target="_blank" rel="noopener"><strong>meta-study</strong></a> which considered this <a href="https://pubmed.ncbi.nlm.nih.gov/16023098/" target="_blank" rel="noopener"><strong>Hardell et al</strong></a> (2006) study.</p>
<p><a href="#_ftnref5" name="_ftn5">[5]</a> As cell phone usage becomes more ubiquitous, and fewer people who have never used a cell phone are available in the population, the exposure will need to be increasingly measured in terms of levels/frequency of usage.</p>
<p><a href="#_ftnref6" name="_ftn6">[6]</a> The additional risk derived using an odds ratio is closely related to the concept of <strong><em>efficacy</em></strong>, which is derived directly from the concept of <strong><em>relative risk</em></strong> (ratio of probabilities). We covered efficacy in an earlier <strong><a href="https://www.kddanalytics.com/covid-vaccine-efficacy-effectiveness/" target="_blank" rel="noopener">article</a></strong>. Epidemiologists typically use relative risk to measure association strength in prospective (cohort) studies; odds ratios in case-control studies.</p>
<p><a href="#_ftnref7" name="_ftn7">[7]</a> Meta-studies start with a larger number of studies.  They then cull studies from the final sample for various reasons, such as data availability and the quality grade they receive.</p>
<p><a href="#_ftnref8" name="_ftn8">[8]</a> All these studies on brain tumors controlled for whether cell phones were being used next to users’ heads.</p>
<p><a href="#_ftnref9" name="_ftn9">[9]</a> <strong><a href="https://seer.cancer.gov/statfacts/" target="_blank" rel="noopener">See</a></strong> for US cancer incidence rates as of 2018.</p>
<p><a href="#_ftnref10" name="_ftn10">[10]</a> See also <a href="https://www.forbes.com/sites/geoffreykabat/2017/12/27/what-the-best-u-s-data-have-to-say-about-brain-cancer-rates/" target="_blank" rel="noopener"><strong>Geoffrey Kabat</strong></a> (2017).</p>
<p>&nbsp;</p>
<p>The post <a href="https://www.kddanalytics.com/if-odds-are-not-odd-what-about-odds-ratios/">If odds are not odd, what about odds ratios?</a> appeared first on <a href="https://www.kddanalytics.com">KDD Analytics</a>.</p>
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