{"id":32144,"date":"2012-10-03T19:04:11","date_gmt":"2012-10-03T23:04:11","guid":{"rendered":"http:\/\/blogs.nejm.org\/cardioexchange\/?post_type=expert-is-in&#038;p=32144"},"modified":"2012-10-03T19:16:32","modified_gmt":"2012-10-03T23:16:32","slug":"crp-and-cholesterol-emerge-as-equally-strong-predictors-of-cardiovascular-risk","status":"publish","type":"post","link":"https:\/\/blogs.nejm.org\/cardioexchange\/2012\/10\/03\/crp-and-cholesterol-emerge-as-equally-strong-predictors-of-cardiovascular-risk\/","title":{"rendered":"CRP and Cholesterol Emerge as Equally Strong Predictors of Cardiovascular Risk"},"content":{"rendered":"<p>In this week&#8217;s issue of the <em>NEJM<\/em>, the Emerging Risk Factors Collaboration, led by Stephen Kaptoge, <a href=\"http:\/\/blogs.nejm.org\/cardioexchange\/news\/what-is-the-benefit-of-adding-crp-to-risk-factor-assessment\/\">present data<\/a> confirming that the inflammatory biomarker C-reactive protein (CRP) provides incremental risk information comparable to that of total cholesterol (TC) and HDL cholesterol (HDL-c). (I am a member of this study group.) The analysis makes four important points.<\/p>\n<div id=\"attachment_32151\" style=\"width: 160px\" class=\"wp-caption alignright\"><a href=\"http:\/\/blogs.nejm.org\/cardioexchange\/wp-content\/uploads\/sites\/7\/2012\/10\/10.1056-NEJMoa1107477Figure012.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-32151\" class=\"size-thumbnail wp-image-32151\" title=\"10.1056-NEJMoa1107477Figure01\" src=\"http:\/\/blogs.nejm.org\/cardioexchange\/wp-content\/uploads\/sites\/7\/2012\/10\/10.1056-NEJMoa1107477Figure012-150x150.jpg\" alt=\"\" width=\"150\" height=\"150\" \/><\/a><p id=\"caption-attachment-32151\" class=\"wp-caption-text\">Click to enlarge<\/p><\/div>\n<p><strong>Point 1:\u00a0<\/strong>As shown in the upper left panel of Figure 1 (right), for a prediction model that already includes age, smoking, systolic blood pressure, and diabetes status, the magnitude of change in the C-statistic associated with adding TC to the model was 0.0043; subsequently adding HDL-c to the latter model changed the C-statistic by 0.0050. These are critical benchmarks for comparison, as all cardiovascular screening programs worldwide include TC and HDL-c.<\/p>\n<p><strong>Point 2:\u00a0<\/strong>Once TC and HDL-c are included in the prediction model, the incremental change in the C-statistic associated with adding CRP was 0.0039, an effect magnitude fully comparable with that of the two prior benchmarks. As each new biomarker is added to a prediction model, the bar it must clear becomes progressively higher. Therefore, these data confirm that CRP\u2019s value in predicting cardiovascular risk is at least similar to that of standard lipid measures. This is borne out by the observation, shown in Table 1, that the multivariable-adjusted hazard ratio associated with a one standard-deviation increase in CRP level was 1.20 (versus 1.17 for a comparable 1-SD increase in TC level). In other words, if on the basis of discrimination and magnitude of effect lipids are considered important for risk prediction, so too must be CRP.<\/p>\n<p><strong>Point 3:\u00a0<\/strong>Compared head-to-head, the incremental predictive value of CRP was modestly greater than that of fibrinogen, and the value of combining the two was broadly similar to that of either alone.<\/p>\n<p><strong>Point 4:\u00a0<\/strong>Most important, by affirming that the role of inflammation in atherothrombosis is comparable to that of cholesterol, these analyses provide support for ongoing trials that target inflammation as a novel treatment strategy. We have recently initiated two large-scale, multinational randomized trials directly testing the inflammatory hypothesis of atherothombosis: one evaluating the interleukin-1-beta inhibitor canakinumab (<a href=\"http:\/\/clinicaltrials.gov\/ct2\/show\/NCT01327846\">CANTOS<\/a>) and the other evaluating low-dose methotrexate (<a href=\"http:\/\/www.thecirt.org\/cirt-summary.html\">CIRT<\/a>). If either or both of these trials are positive, we will have direct evidence that reducing inflammation reduces vascular risk.<\/p>\n<p>Whether clinicians ought to use any biomarkers for risk prediction should be based on hard trial evidence and on the concepts of <a href=\"http:\/\/circoutcomes.ahajournals.org\/content\/5\/4\/592.full\">\u201cwhat works?\u201d and \u201cin whom?\u201d<\/a>. In primary prevention, randomized trials have shown statins to be highly effective at reducing event rates among patients with elevated LDL-c levels (<a href=\"http:\/\/www.nejm.org\/doi\/full\/10.1056\/NEJMoa065994\">WOSCOPS<\/a>), low HDL-c levels (<a href=\"http:\/\/www.nejm.org\/doi\/full\/10.1056\/NEJM200106283442601\">AFCAPS\/TexCAPS<\/a>), and elevated CRP levels (<a href=\"http:\/\/www.nejm.org\/doi\/full\/10.1056\/NEJMoa0807646\">JUPITER<\/a>). A simple set of evidence-based prevention guidelines, derived from these hard trial outcomes, is easy to follow.<\/p>\n<p><em><strong>Disclosure:<\/strong> Dr. Ridker, a member of <a href=\"http:\/\/www.nejm.org\/doi\/full\/10.1056\/NEJMoa1107477\">the Emerging Risk Factors Collaboration<\/a>, is listed as a co-inventor on patents, held by Brigham and Women\u2019s Hospital (BWH), that relate to the use of inflammatory biomarkers licensed to AstraZeneca and Siemens. He is also the principal investigator of the NHLBI-supported <a href=\"http:\/\/www.thecirt.org\/paul-m-ridker-md-mph--bwh.html\">CIRT trial<\/a> and the Novartis-supported <a href=\"http:\/\/clinicaltrials.gov\/ct2\/show\/NCT01327846\">CANTOS trial<\/a>. However, neither Dr. Ridker nor the BWH receives any royalties related to these patents for use of the CRP test in either clinical trial.<\/em><\/p>\n<p><strong>Share your thoughts on the CRP findings from the Emerging Risk Factors Collaboration.<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Paul Ridker discusses findings from the Emerging Risk Factors Collaboration showing that C-reactive protein provides incremental risk information comparable to that of total cholesterol and HDL cholesterol.<\/p>\n","protected":false},"author":433,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7],"tags":[953,1428,210,212,1489],"class_list":["post-32144","post","type-post","status-publish","format-standard","hentry","category-prevention","tag-c-reactive-protein","tag-cardiovascular-risk-prediction","tag-cholesterol","tag-crp","tag-inflammatory-markers"],"_links":{"self":[{"href":"https:\/\/blogs.nejm.org\/cardioexchange\/wp-json\/wp\/v2\/posts\/32144","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.nejm.org\/cardioexchange\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.nejm.org\/cardioexchange\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.nejm.org\/cardioexchange\/wp-json\/wp\/v2\/users\/433"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.nejm.org\/cardioexchange\/wp-json\/wp\/v2\/comments?post=32144"}],"version-history":[{"count":0,"href":"https:\/\/blogs.nejm.org\/cardioexchange\/wp-json\/wp\/v2\/posts\/32144\/revisions"}],"wp:attachment":[{"href":"https:\/\/blogs.nejm.org\/cardioexchange\/wp-json\/wp\/v2\/media?parent=32144"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.nejm.org\/cardioexchange\/wp-json\/wp\/v2\/categories?post=32144"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.nejm.org\/cardioexchange\/wp-json\/wp\/v2\/tags?post=32144"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}