<h2>Smell loss is one of the burdensome symptoms CRSwNP patients</h2>
<p>Loss of smell is is one of the most troublesome and difficult-to-treat symptoms of severe CRSwNP, while it is reported in by 90 % of patients (Figure 1).<sup>1</sup></p>

<p>In an international patient experience survey (n=107) demonstrated that olfactory dysfunction was the most impactful symptoms on patients quality of life with 71 % of respondents stating a loss/reduced sense of smell as problem to be “as bad as it can be” (Figure 2).<sup>2</sup></p>

<h2>Understanding smell impairment in CRSwNP patients: expert interview with Sanna Salmi</h2>
<p>Join <strong>Professor Sanna Salmi</strong>, Professor of Otorhinolaryngology at the University of Eastern Finland, as she explores how smell impairment affects patients' quality of life and shares practical perspectives on managing it in clinical practice.</p>

<h3>Key Topics Covered</h3>
<ul>
 <li>Significance of smell impairment for patients</li>
 <li>Mechanisms of smell impairment</li>
 <li>Smell assessment and clinical considerations</li>
</ul>

<p>Loss of sense of smell is a common symptom of chronic rhinosinusitis with nasal polyps (CRSwNP), but its impact is often underestimated. Learn how olfactory dysfunction affects patient’s quality of life and explore the underlying mechanisms driving smell loss in CRSwNP.</p>

SPECIALTY-CARE

DUPIXENT

CHRONIC-RHINOSINUSITIS-WITH-NASAL-POLYPS-CRSWNP

RESPIRATORY

Loss of Smell in CRSwNP

<h2>Olfactory dysfunction</h2>
<p>In a study of CRS patients with different inflammatory endotypes (n=230), loss of smell was associated with the type 2 endotype.<sup>3</sup> Moreover, type 2 inflammation is associated with smell loss in CRSwNP via <strong>conductive</strong> and <strong>sensorineural olfactory dysfunction</strong> (Figure 3).<sup>4</sup> In conductive disease, physical airflow obstructions prevent odorants from reaching the olfactory epithelium in the nasal cavity, while in sensorineural disease, olfactory receptor signalling to the brain is impaired.<sup>5-7</sup></p>

<h2>The role of cytokines in the CRSwNP pathophysiology</h2>
<p>Elevated levels of type 2 inflammatory cytokines, IL-4, IL-13, IL-5, thymic stromal lmphopoietin (TSLP), eoxatin-3 and periostin have been correlated with a decline in olfactory function.</p>
<p>Therapies that target IL-4, IL-5, IL-13 and TSLP have provided significant improvements to the sense of smell, and reductions in nasal polyps and nasal congestion in phase 3 trials, highlighting the importance of type 2 inflammatory cytokines as valuable targets for improving the symptom burden of patients with CRSwNP (Figure 4).<sup>8,9,10,11</sup></p>

<h2>Smell loss was investigated in DUPIREAL real-world study</h2>
<p>DUPIREAL is the largest real-life study (more than 900 patients) evaluating effectiveness of dupilumab (including treatment response, disease control and remission) in CRSwNP over 2 years in a real-life setting.<sup>12</sup> Olfactory functioning improved over time, as indicated by a significant increase in Sniffin’ Sticks score (p&lt;0.001) and a significant reduction in smell VAS score (p&lt;0.001) compared to baseline (Figure 5).<sup>12</sup></p>

<h3 style="text-align:center;">Primary and selected secondary outcomes:</h3>

<h3>Mechanisms of Olfactory Dysfunction in CRSwNP</h3>
<p>Read more on the underlying mechanisms of olfactory dysfunction in CRSwNP, including how type 2 inflammation drives both conductive and sensorineural disruptions that lead to the severe smell loss.</p>

<h3>Diagnostic Approaches for Smell Assessment in CRSwNP</h3>
<p>Read more on the prevalence and clinical burden of smell loss in CRSwNP patients, why olfactory dysfunction remains underassessed in practice, and which validated diagnostic tools (Sniffin' Sticks, UPSIT, and VAS) are recommended by current guidelines for routine olfactory assessment.</p>

<h3>Uncovering the hidden burden: Understanding loss of smell in CRSwNP</h3>
<p>The loss of sense of smell is a common symptom of chronic rhinosinusitis with nasal polyps (CRSwNP); however, its impact is often underestimated. To increase understanding on smell loss, Sanofi and EUFOREA have produced a Smell booklet, a short guidebook discussing mechanisms, impact, and assessment of olfactory disfunction.</p>

<p>Referenties</p>

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Loss of sense of smell is a common symptom of chronic rhinosinusitis with nasal polyps (CRSwNP), but its impact is often underestimated. Learn how olfactory dysfunction affects patient’s quality of life and explore the underlying mechanisms driving smell loss in CRSwNP.

<p>PCSK9i mAb therapy use was associated with a lower rate of ischaemic events and mortality rates vs. no PCSK9i* in a study of over 19,000 ASCVD patients without prior ischaemic events.<sup>1</sup></p>
<p>Discover the findings from the <strong>methodologically advanced<sup>+</sup> real-world OPTIMUS-CLASS study</strong>, part of the broader OPTIMUS (Outcomes and PrevenTlon Programme with PCSK9i Monoclonal Antibodies in ASCVD PopUlation without Prior ISchaemic Events) programme.<sup>1,2</sup></p>

<h3>Patients with ASCVD but no history of an ischaemic event who initiated a PCSK9i mAb<sup>‡</sup> saw a:</h3>
<p><strong>30.9%</strong> 5-year relative risk reduction in ischaemic events and all-cause mortality vs. no PCSK9i* P&lt;0.0001 (ARR 7.8%).<sup>1</sup></p>

<ul>
 <li>All patients with ASCVD are at <strong>very high or extreme risk of a potentially fatal CV event</strong><sup>3</sup></li>
 <li><strong>LDL-C is the primary target</strong> for CV risk reduction and PCSK9 inhibitors can reduce LDL-C levels when used alone or in combination with statins<sup>3,4</sup></li>
 <li>While clinical trials have established the effectiveness of PCSK9i mAbs across the different stages of ASCVD, <strong>real-world data remain limited</strong><sup>1</sup></li>
 <li>The OPTIMUS-CLASS study provides <strong>real-world evidence</strong> on the 5-year impact of PCSK9i mAbs<sup>‡</sup> on ischaemic events and all-cause mortality in ASCVD patients without any prior ischaemic events<sup>1</sup></li>
</ul>

<p>Retrospective, real-world, propensity score-matched database review<sup>1</sup></p>

<p>Compare the incidence of composite of nonfatal MI, nonfatal IS or all-cause mortality at 5 years with PCSK9i mAb<sup>‡</sup> vs. no PCSK9i* in ASCVD patients without a prior ischaemic event<sup>1</sup></p>

<ul><li>Patients with ASCVD (N=19,670), without a history of ischaemic events, were identified through the US Optum Research Database<sup>1¥</sup></li><li>Patients who initiated treatment with a PCSK9i mAb<sup>‡</sup> (n=6,545) from Jan 2016-Dec 2022 were identified and a 1:2 propensity score-matched comparator cohort of PCSK9i non-initiators was developed<sup>1</sup></li></ul>

<p>Composite representing first occurrence of nonfatal MI, nonfatal IS or all-cause mortality<sup>1</sup></p>

<p>G-computation, a statistical approach used to reduce bias in observational analyses, was applied to estimate the incidence of the primary endpoint over time<sup>1</sup></p>

<ul><li>Individual endpoints of nonfatal MI, nonfatal IS and all-cause mortality<sup>1</sup></li><li>LDL-C reduction from baseline in patients in the PCSK9i mAb<sup>‡</sup> group<sup>1</sup></li></ul>

<p>The baseline characteristics for the PCSK9i mAb<sup>‡</sup> group and no PCSK9i* group were <strong>well balanced</strong>.1</p>

<figure class="table" style="width:100%;">
 <table style="background-color:#fff;border-color:#fff;border-style:solid;">
  <tbody>
   <tr>
    <td style="background-color:#004350;border-color:#fff;padding:10px;width:25%;">&nbsp;</td>
    <td style="background-color:#004350;border-color:#fff;padding:10px;width:25%;">
     <h4><span style="color:hsl(0, 0%, 100%);">PCSK9i mAb<sup>‡</sup></span><br><span style="color:hsl(0, 0%, 100%);">(n=6,545)</span></h4></td>
    <td style="background-color:#004350;border-color:#fff;padding:10px;width:25%;">
     <h4><span style="color:hsl(0, 0%, 100%);">No PCSK9i*</span><br><span style="color:hsl(0, 0%, 100%);">(n=13,125)</span></h4></td>
    <td style="background-color:#004350;border-color:#fff;padding:10px;width:25%;">
     <h4><span style="color:hsl(0, 0%, 100%);">Total</span><br><span style="color:hsl(0, 0%, 100%);">(N=19,670)</span></h4></td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">Male (%)</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">50.8</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">50.7</td>
    <td style="border-color:#fff;padding:10px;">50.7</td>
   </tr>
   <tr>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">Age</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">&nbsp;</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">&nbsp;</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">&nbsp;</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">18-44</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">1.3</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">1.7</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">1.6</td>
   </tr>
   <tr>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">45-64</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">30.7</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">30.8</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">30.8</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">65+</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">68.0</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">67.5</td>
    <td style="border-color:#fff;padding:10px;">67.6</td>
   </tr>
   <tr>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">Insurance</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">&nbsp;</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">&nbsp;</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">&nbsp;</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">- Medicare Advantage<sup>¥</sup></td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">68.1</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">69.8</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">69.3</td>
   </tr>
   <tr>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">- Commercial</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">31.9</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">30.2</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">30.7</td>
   </tr>
  </tbody>
 </table>
</figure>
<p data-font="small">Adapted from Bhatt et al. 2026.</p>

Demographics (%)

<figure class="table" style="width:100%;">
 <table style="background-color:#fff;border-color:#fff;border-style:solid;">
  <tbody>
   <tr>
    <td style="background-color:#08A6CA;border-color:#fff;padding:10px;width:25%;">&nbsp;</td>
    <td style="background-color:#08A6CA;border-color:#fff;padding:10px;width:25%;">
     <h4><span style="color:hsl(0, 0%, 100%);">PCSK9i mAb<sup>‡</sup></span><br><span style="color:hsl(0, 0%, 100%);">(n=6,545)</span></h4></td>
    <td style="background-color:#08A6CA;border-color:#fff;padding:10px;width:25%;">
     <h4><span style="color:hsl(0, 0%, 100%);">No PCSK9i*</span><br><span style="color:hsl(0, 0%, 100%);">(n=13,125)</span></h4></td>
    <td style="background-color:#08A6CA;border-color:#fff;padding:10px;width:25%;">
     <h4><span style="color:hsl(0, 0%, 100%);">Total</span><br><span style="color:hsl(0, 0%, 100%);">(N=19,670)</span></h4></td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">Coronary Conditions</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">76.7</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">76.0</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">76.1</td>
   </tr>
   <tr>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">- Stable Angina</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">74.7</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">73.5</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">73.8</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">- Other IHD</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">17.3</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">17.2</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">17.2</td>
   </tr>
   <tr>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">- Prior Revascularisation</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">25.6</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">25.5</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">25.5</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">- PCI</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">16.7</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">16.4</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">16.5</td>
   </tr>
   <tr>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">- CABG</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">12.0</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">11.9</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">11.9</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">Ischaemic cerebrovascular disease</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">9.4</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">9.6</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">9.6</td>
   </tr>
   <tr>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">Peripheral artery disease</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">19.1</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">19.4</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">19.3</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">- Lower extremities</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">3.9</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">4.1</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">4.0</td>
   </tr>
   <tr>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">- Aorta</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">4.9</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">4.9</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">4.9</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">- Other<span style="background-color:rgb(255,255,255);color:rgb(0,0,0);"><sup>II</sup></span></td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">10.3</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">10.4</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">10.4</td>
   </tr>
  </tbody>
 </table>
</figure>
<p data-font="small">Adapted from Bhatt et al. 2026.</p>

ASCVD characteristics (%)

<figure class="table" style="width:100%;">
 <table style="background-color:#fff;border-color:#fff;border-style:solid;">
  <tbody>
   <tr>
    <td style="background-color:#004350;border-color:#fff;padding:10px;width:25%;">&nbsp;</td>
    <td style="background-color:#004350;border-color:#fff;padding:10px;width:25%;">
     <h4><span style="color:hsl(0, 0%, 100%);">PCSK9i mAb<sup>‡</sup></span><br><span style="color:hsl(0, 0%, 100%);">(n=6,545)</span></h4></td>
    <td style="background-color:#004350;border-color:#fff;padding:10px;width:25%;">
     <h4><span style="color:hsl(0, 0%, 100%);">No PCSK9i*</span><br><span style="color:hsl(0, 0%, 100%);">(n=13,125)</span></h4></td>
    <td style="background-color:#004350;border-color:#fff;padding:10px;width:25%;">
     <h4><span style="color:hsl(0, 0%, 100%);">Total</span><br><span style="color:hsl(0, 0%, 100%);">(N=19,670)</span></h4></td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">Diabetes</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">35.9</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">35.8</td>
    <td style="border-color:#fff;padding:10px;">35.9</td>
   </tr>
   <tr>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">- No insulin</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">23.9</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">23.8</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">23.9</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">- On insulin</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">12.0</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">12.0</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">12.0</td>
   </tr>
   <tr>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">Hypertension</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">79.5</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">79.5</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">79.5</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">Liver disease</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">5.1</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">5.2</td>
    <td style="border-color:#fff;padding:10px;">5.2</td>
   </tr>
   <tr>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">COPD</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">9.9</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">9.9</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">9.9</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">Heart failure</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">8.7</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">8.5</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">8.6</td>
   </tr>
   <tr>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">Chronic kidney disease</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">10.7</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">10.4</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">10.4</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">- Stage III</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">9.2</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">8.9</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">8.9</td>
   </tr>
   <tr>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">- Stage IV<sup>¶</sup></td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">1.5</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">1.5</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">1.5</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">Atrial fibrillation</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">9.7</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">9.7</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">9.7</td>
   </tr>
   <tr>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">Tobacco use</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">17.6</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">17.7</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">17.6</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">Cancer</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">11.9</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">11.3</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">11.4</td>
   </tr>
   <tr>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">- Diagnosis</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">8.9</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">9.0</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">8.9</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">- Medication</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">4.8</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">4.6</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">4.6</td>
   </tr>
  </tbody>
 </table>
</figure>
<p data-font="small">Adapted from Bhatt et al. 2026.</p>

Other comorbidities (%)

<figure class="table" style="width:100%;">
 <table style="background-color:#fff;border-color:#fff;border-style:solid;">
  <tbody>
   <tr>
    <td style="background-color:#08A6CA;border-color:#fff;padding:10px;width:25%;">&nbsp;</td>
    <td style="background-color:#08A6CA;border-color:#fff;padding:10px;width:25%;">
     <h4><span style="color:hsl(0, 0%, 100%);">PCSK9i mAb<sup>‡</sup></span><br><span style="color:hsl(0, 0%, 100%);">(n=6,545)</span></h4></td>
    <td style="background-color:#08A6CA;border-color:#fff;padding:10px;width:25%;">
     <h4><span style="color:hsl(0, 0%, 100%);">No PCSK9i*</span><br><span style="color:hsl(0, 0%, 100%);">(n=13,125)</span></h4></td>
    <td style="background-color:#08A6CA;border-color:#fff;padding:10px;width:25%;">
     <h4><span style="color:hsl(0, 0%, 100%);">Total</span><br><span style="color:hsl(0, 0%, 100%);">(N=19,670)</span></h4></td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">LLT use during 1-year prior to index, %</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">&nbsp;</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">&nbsp;</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">&nbsp;</td>
   </tr>
   <tr>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">Any statin use</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">61.0</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">61.6</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">61.4</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">- Low-intensity</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">5.5</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">6.5</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">6.2</td>
   </tr>
   <tr>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">- Moderate-intensity</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">23.8</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">25.9</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">25.3</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">- High-intensity</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">31.7</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">29.3</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">29.9</td>
   </tr>
   <tr>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">Ezetimibe</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">33.4</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">33.3</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">33.3</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">Ezetimibe w/o statin</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">11.3</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">11.0</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">11.1</td>
   </tr>
   <tr>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">Icosapent ethyl</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">3.1</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">3.0</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">3.0</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">Bempedoic acid</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">0.4</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">0.5</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">0.5</td>
   </tr>
   <tr>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">Any statin, ezetimibe or bempedoic acid</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">72.4</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">72.7</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">72.6</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">Other CV SOC during 1-year prior to Index, %</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">&nbsp;</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">&nbsp;</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">&nbsp;</td>
   </tr>
   <tr>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">Beta-blockers</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">52.6</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">52.3</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">52.4</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">ACEi / ARB</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">58.2</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">58.1</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">58.1</td>
   </tr>
   <tr>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">Antiplatelets<sup>**</sup></td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">23.8</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">23.5</td>
    <td style="background-color:#f4f2f6;border-color:#fff;padding:10px;">23.6</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">Anticoagulants</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">10.5</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">10.5</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">10.5</td>
   </tr>
  </tbody>
 </table>
</figure>
<p data-font="small">Adapted from Bhatt et al. 2026.</p>

Medications (%)

<figure class="table" style="width:100%;">
 <table style="background-color:#fff;border-color:#fff;border-style:solid;">
  <tbody>
   <tr>
    <td style="background-color:#004350;border-color:#fff;padding:10px;width:25%;">&nbsp;</td>
    <td style="background-color:#004350;border-color:#fff;padding:10px;width:25%;">
     <h4><span style="color:hsl(0, 0%, 100%);">PCSK9i mAb<sup>‡</sup></span><br><span style="color:hsl(0, 0%, 100%);">(n=6,545)</span></h4></td>
    <td style="background-color:#004350;border-color:#fff;padding:10px;width:25%;">
     <h4><span style="color:hsl(0, 0%, 100%);">No PCSK9i*</span><br><span style="color:hsl(0, 0%, 100%);">(n=13,125)</span></h4></td>
    <td style="background-color:#004350;border-color:#fff;padding:10px;width:25%;">
     <h4><span style="color:hsl(0, 0%, 100%);">Total</span><br><span style="color:hsl(0, 0%, 100%);">(N=19,670)</span></h4></td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">Mean (SD), mmol/L</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">3.0 (1.1)</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">3.0 (1.1)</td>
    <td style="border-color:#fff;padding:10px;">3.0 (1.1)</td>
   </tr>
   <tr>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">Mean (SD), mg/dL</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">117.8 (42.0)</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">116.1 (43.2)</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">116.5 (42.9)</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">Median, mmol/L</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">3.1</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">2.9</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">2.9</td>
   </tr>
   <tr>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">Median, mg/dL</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">118.0</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">112.0</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">113.0</td>
   </tr>
  </tbody>
 </table>
</figure>
<p data-font="small">Adapted from Bhatt et al. 2026.</p>

LDL-C measures (%)

GENERAL-MEDICINES

DYSLIPIDEMIA

CARDIOLOGY

<p>PCSK9i mAb<sup>‡</sup> treatment was associated with a <strong>30.9% relative reduction in the risk of</strong> nonfatal MI, nonfatal IS or all-cause mortality in ASCVD patients without a prior ischaemic event.<sup>1</sup></p>
<p>The estimated 5-year event rate for the composite endpoint of nonfatal MI, nonfatal IS or all-cause mortality was significantly lower in the PCSK9i mAb<sup>‡</sup> group vs. the no PCSK9i* group.<sup>1</sup></p>
<p>The 5-year event rate was 17.5% (95% CI 15.5, 19.5) in the PCSK9i mAb<sup>‡</sup> group (n=6,545) vs. 25.4% (95% CI 23.6, 27.1) in the no PCSK9i* group (n=13,125), resulting in a significant 30.9% relative reduction in the risk of first MACE (ARR 7.8%) (P&lt;0.0001).<sup>1</sup></p>
<h3 style="text-align:center;">Estimated event rates over time for the primary endpoint with parametric G-formula (ITT)<sup>1</sup></h3>

<p>A reduction in 5-year event rate was also seen in the PCSK9i mAb<sup>‡</sup> group across each individual endpoint, with 28.3%, 26.4% and 28.5% RRR observed across nonfatal MI, nonfatal IS and all-cause mortality event rates, respectively, vs. the no PCSK9i* group.<sup>5</sup></p>
<h3 style="text-align:center;">Individual endpoint 5-year event rates (ITT)<sup>5</sup></h3>

<figure class="table" style="width:100%;">
 <table class="ck-table-resized" style="background-color:#fff;border-color:#fff;border-style:solid;">
  <colgroup>
   <col style="width:20%;">
   <col style="width:20%;">
   <col style="width:20%;">
   <col style="width:20%;">
   <col style="width:20%;">
  </colgroup>
  <tbody>
   <tr>
    <td style="background-color:#004350;border-color:#fff;padding:10px;width:20%;">&nbsp;</td>
    <td style="background-color:#004350;border-color:#fff;padding:10px;width:20%;">
     <h4><span style="color:hsl(0, 0%, 100%);">PCSK9i mAb<sup>‡</sup></span><br><span style="color:hsl(0, 0%, 100%);">5-year event rate</span><br><span style="color:hsl(0, 0%, 100%);">(%, 95% CI)</span></h4></td>
    <td style="background-color:#004350;border-color:#fff;padding:10px;width:20%;">
     <h4><span style="color:hsl(0, 0%, 100%);">No PCSK9i*</span><br><span style="color:hsl(0, 0%, 100%);">5-year event rate</span><br><span style="color:hsl(0, 0%, 100%);">(%, 95% CI)</span></h4></td>
    <td style="background-color:#004350;border-color:#fff;padding:10px;width:20%;">
     <h4><span style="color:hsl(0, 0%, 100%);">RRR</span><br><span style="color:hsl(0, 0%, 100%);">(%, 95% CI)</span></h4></td>
    <td style="background-color:#004350;border-color:#fff;padding:10px;width:20%;">
     <h4><span style="color:hsl(0, 0%, 100%);">ARR</span><br><span style="color:hsl(0, 0%, 100%);">(%, 95% CI)</span></h4></td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">Nonfatal MI</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">5.2 (4.3, 6.3)</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">7.3 (6.6, 8.1)</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">28.3 (12.0, 40.6<br>
      [P&lt;0.0001])</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">2.1 (0.8, 3.1<br>
      [P&lt;0.0001])</td>
   </tr>
   <tr>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">Nonfatal IS</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">4.0 (3.1,4.7)</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">5.4 (4.6, 6.3)</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">26.4 (6.5, 45.7<br>
      [P=0.02])</td>
    <td style="background-color:#d9e3e5;border-color:#fff;padding:10px;">1.5 (0.3, 2.7<br>
      [P=0.02])</td>
   </tr>
   <tr>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">All-cause mortality</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">8.7 (7.5, 9.8)</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">12.2 (11.2, 13.0)</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">28.5 (16.6, 39.1<br>
      [P&lt;0.0001])</td>
    <td style="background-color:#fff;border-color:#fff;padding:10px;">3.5 (2.0, 4.9<br>
      [P&lt;0.0001])</td>
   </tr>
  </tbody>
 </table>
</figure>
<p data-font="small">Adapted from Bhatt et al. 2026. Supplementary Material.</p>

<p>In the ITT population, patients in the PCSK9i mAb<sup>‡</sup> group went from an LDL-C level of 117.8 mg/dL to 78.0 mg/dL at follow-up after 5 years.<sup>1</sup> This resulted in a 39.8 mg/dL absolute reduction in LDL-C, representing a 33.8% percentage reduction.<sup>1</sup> <strong>These findings are consistent with the CTT<sup>††</sup>,</strong> which demonstrated a strong association between RRR in MACE per 1 mmol/L reduction in LDL-C.<sup>6</sup></p>
<h3 style="text-align:center;">Relationship between LDL-C reduction and relative risk reduction in ischaemic events compared to CTT meta-analysis<sup>1</sup></h3>

<p>When looking at patients who were treated with or without statins, both the with statins and without statins PCSK9i mAb<sup>‡</sup> groups had lower cumulative event rates than their equivalent no PCSK9i* groups.<sup>5 </sup>Current study 30.9% (95% CI 22.3%, 38.1), CTT RRR 28.8% (95% CI 22.6%, 35.0%)</p>
<p><strong>The falsification analysis, used to support the validity of data, found no significant difference between the PCSK9i mAb<sup>‡</sup> and no PCSK9i* groups.<sup>1</sup></strong></p>
<p>To help determine whether the lower rate of MACE with PCSK9i mAbs<sup>‡</sup> VS. no PCSK9i* was confounded by other factors, the study assessed whether PCSK9i mAbs<sup>‡</sup> vs. no PCSK9i* was associated with any unexpected benefit in the falsification endpoint, defined as composite of cancer, hospitalised major bleeding or hospitalised sepsis.<sup>1</sup> At 5 years, the incidence of the falsification endpoint was similar in the PCSK9i mAbs<sup>‡</sup> group (9.1%) and no PCSK9i* group (10.2%), supporting the validity of the MACE data.<sup>1</sup></p>
<h3 style="text-align:center;">Falsification analysis<sup>1</sup></h3>

<h3>In ASCVD patients without prior ischaemic events, PCSK9i mAb<sup>‡</sup> therapy compared with no PCSK9i* treatment was associated with a relative reduction in the risk of ischaemic events or mortality.<sup>1</sup></h3>

<p data-font="small">*No PCSK9i represents no PCSK9 monoclonal antibodies (alirocumab or evolocumab) or PCSK9 small interfering RNA (inclisiran).<sup>1</sup>&nbsp;<br>
  +RWE studies can vary substantially in their methodological approaches, which may contribute to heterogeneity or unexpected findings across analyses. Ensuring that key epidemiological principles – such as appropriate time zero definition, new user design considerations, handling of open claims data, and assessment of potential time related biases – are rigorously applied remains essential to generate reliable insights. High quality RWE therefore depends on robust and methodically advanced approaches such as propensity score matching and G-computation used in the study.&nbsp;<br>
  ‡PCSK9i mAb represents alirocumab or evolocumab.<sup>1</sup>&nbsp;<br>
  ¥A claims database, representing an insured population in the US.<sup>1</sup>&nbsp;<br>
  §Represents health plan in the US offered by a private company that contracts with Medicare to provide patients with hospital and medical insurance benefits.<sup>1</sup>&nbsp;<br>
  ||Includes any type of disease that is non-coronary, non-cerebrovascular, or does not involve the lower extremities or aorta.<sup>1</sup>&nbsp;<br>
  ¶Includes dialysis or renal transplant.<sup>1</sup>&nbsp;<br>
  **Includes clopidogrel, ticagrelor, and prasugrel; 98.8% use in this category was for these agents. Additional agents were anagrelide, cilostazol, dipyridamole (including aspirin combo), pentoxifylline and vorapaxar sulphate.<sup>1</sup>&nbsp;<br>
  ++CTT relative risk reduction = 28% (95% CI 22, 34) per mmol/L reduction in LDL-C.<sup>1</sup></p>

<p>Indication &amp; dosing information</p>

PCSK9 inhibitor treatment and outcomes

<p>9/10 patients with severe asthma have underlying type 2 inflammation.<sup>2,*</sup> This disease progression may be prevented by early targeted treatment of the inflammation.<sup>3</sup></p>

<h2>The importance of early targeted intervention in T2 Asthma<sup>2</sup></h2>
<p>Early treatment of type 2 Asthma with biologics:</p>

<p>Prevents OCS-use and associated adverse events<sup>3</sup></p>

<p>May prevent irreversible damage of lung tissue<sup>3</sup></p>

<p>May increase the chance of remission<sup>3</sup></p>

<h3>Listen to Prof. Alberto Papi about the importance of early intervention</h3>

<h2>Type 2 biomarkers as predictive tools for assessing Asthma Attack</h2>

<figure class="table" style="width:100%;">
 <table style="background-color:#e4e4e4;border-color:#fff;border-style:solid;">
  <tbody>
   <tr>
    <td style="background-color:#e4e4e4;border-color:#fff;padding:20px;">
     <h3>Type 2 inflammation can be identified by two independent and complementary biomarkers:</h3>
     <ul>
      <li>Blood eosinophil count (EOS), and</li>
      <li>Elevated fractional exhaled nitric oxide levels (FeNO)<sup>1</sup></li>
     </ul></td>
   </tr>
  </tbody>
 </table>
</figure>

<p>FeNO and blood eosinophils serve as more than diagnostic markers: they are predictive indicators of disease progression and treatment response.<sup>4,5</sup></p>
<p>Patients at risk of exacerbations can already be identified at an early stage with these 2 biomarkers.<sup>1</sup></p>

<figure class="table" style="width:100%;">
 <table style="background-color:#23004c;border-color:#fff;border-style:solid;">
  <tbody>
   <tr>
    <td style="background-color:#7A00E6;border-color:#7A00E6;padding:10px;text-align:center;">
     <h3><span style="color:hsl(0,0%,100%);">Did you know?</span></h3></td>
   </tr>
   <tr>
    <td style="background-color:#23004c;border-color:#23004c;padding:20px;">
     <h3><span style="color:hsl(0,0%,100%);">Combined elevated EOS and FeNO levels even indicate a 2-fold risk-increase of severe asthma attacks compared to lower levels.<sup>1</sup></span></h3></td>
   </tr>
  </tbody>
 </table>
</figure>

<h2>Targeted Asthma treatment with biologics<sup>2</sup></h2>
<p>Where oral corticosteroids (OCS) primarily target symptoms, biologics specifically inhibit key cytokines involved in the inflammatory process (e.g. IL-4 and IL-13).<sup>6,7</sup> Combined with biomarkers, this allows for a personalized treatment and monitoring approach.<sup>8,9</sup> Importantly, biologics can not only reduce symptoms but may also modify the disease course.<sup>2</sup></p>

<p>Reduce corticosteroid use and associated adverse events<sup>10</sup></p>

<p>Reduced exacerbations and improved lung function<sup>10,11</sup></p>

<p>Personalized treatment approach<sup>11</sup></p>

<p>Lower emergency department visit and healthcare burden<sup>12</sup></p>

<h3>Learn more about key cytokines with Prof. Lipworth’s explanatory video</h3>

<p>The OCS Trap: Understanding the Risks Short-term and Long-term Consequences<sup>6</sup></p>

<h2>The first OCS burst is the first sign to assess for type 2 asthma<sup>4,14-16</sup></h2>
<p>The GINA guideline recommends early initiation of biologic treatment in patients with asthma and the following type 2 inflammation characteristics:<sup>4</sup></p>

<p>Blood eosinophil ≥150/μL and or sputum eosinophil level ≥2%<sup>4</sup></p>

<p>Clinically allergen-driven asthma<sup>4</sup></p>

<p>It is important to note that mOCS can suppress these biomarkers, making detection challenging. Therefore, biomarker testing should be repeated up to three times, ideally 1-2 weeks after OCS discontinuation or on the lowest possible OCS dose.<sup>4,5</sup></p>
<p>The GINA guideline furthermore recommends:<sup>4</sup></p>
<ul>
 <li>Proactive phenotyping using biomarker assessment</li>
 <li>Early initiation of biologics before OCS dependency develops</li>
 <li>Systematic OCS tapering in patients receiving maintenance therapy</li>
 <li>Regular monitoring and treatment optimization</li>
</ul>

<figure class="table" style="width:100%;">
 <table style="background-color:#23004c;border-color:#fff;border-style:solid;">
  <tbody>
   <tr>
    <td style="background-color:#7A00E6;border-color:#7A00E6;padding:10px;text-align:center;">
     <h3><span style="color:hsl(0,0%,100%);">Key message</span></h3></td>
   </tr>
   <tr>
    <td style="background-color:#23004c;border-color:#23004c;padding:20px;">
     <h3><span style="color:hsl(0,0%,100%);">Early assessment of the EOS and FeNO biomarkers and targeted treatment of type 2 inflammation with biologicals can improve the trajectory of asthma progression in your patients.</span></h3></td>
   </tr>
  </tbody>
 </table>
</figure>
<p data-font="small">*Up to 88% of adult patients may have T2 inflammation. T2 inflammation is defined as 1 of 3 phenotypes: eosinophilic asthma (blood eosinophils ≥150 cells/μL); atopic asthma allergen-specific IgE ≥0.35 IU/mL for any of 9 perennial allergens); Th2-high asthma (total serum IgE ≥100 IU/mL + blood eosinophils ≥140 cells/μL).<sup>1</sup></p>

Biomarkers in Asthma: Early Intervention with Precision Medicine

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