How to Identify Type 2 Chronic Rhinosinusitis in East Asian Patients

Shin Hyuk Yoo; Ki-Il Lee; Gwanghui Ryu; Jun-Sang Bae; Ji-Hun Mo

doi:10.18787/jr.2026.00004

J Rhinol > Volume 33(1); 2026

Yoo, Lee, Ryu, Bae, and Mo: How to Identify Type 2 Chronic Rhinosinusitis in East Asian Patients

Review

Journal of Rhinology 2026;33(1):11-20.

Published online: March 31, 2026

DOI: https://doi.org/10.18787/jr.2026.00004

How to Identify Type 2 Chronic Rhinosinusitis in East Asian Patients

Shin Hyuk Yoo, MD, PhD^1,^2,^*

, Ki-Il Lee, MD, PhD^3,^*

, Gwanghui Ryu, MD, PhD^4,^*

, Jun-Sang Bae, PhD^1,⁴

, Ji-Hun Mo, MD, PhD^1,⁴

¹Department of Otorhinolaryngology, Dankook University College of Medicine, Cheonan, Republic of Korea

²Dankook Institution of Medical and Optics (DIMO), Dankook University College of Medicine, Cheonan, Republic of Korea

³Department of Otorhinolaryngology-Head and Neck Surgery, Konyang University College of Medicine, Daejeon, Republic of Korea

⁴Department of Otorhinolaryngology-Head and Neck Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

Address for correspondence: Ji-Hun Mo, MD, PhD, Department of Otorhinolaryngology, Dankook University College of Medicine, 201 Manghyang-ro, Dongnam-gu, Cheonan 31116, Republic of Korea,
Tel: +82-41-550-3933, Fax: +82-41-556-1090, E-mail: jihunmo@gmail.com

*These authors contributed equally to this work.

Received January 25, 2026 Revised March 1, 2026 Accepted March 16, 2026

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Chronic rhinosinusitis (CRS) is increasingly recognized as a heterogeneous disease with distinct inflammatory endotypes, among which eosinophilic CRS (ECRS)—a category that substantially overlaps with, but is not equivalent to, Type 2 CRS—is associated with severe symptoms, frequent recurrence, and comorbid asthma. Accurate identification of Type 2 CRS has become clinically essential with the emergence of biologic therapies that target Type 2 inflammatory pathways. However, most diagnostic criteria, including those proposed by European Position Paper on Rhinosinusitis and Nasal Polyps 2020 (EPOS 2020), were developed from Western populations, in which ECRS with nasal polyps predominates. This review critically examines the applicability of these criteria in Asian populations, in which non-eosinophilic and mixed inflammatory endotypes remain prevalent. Evidence from Korean and Japanese cohorts indicates that the EPOS 2020 Type 2 criteria have poor specificity in Asian patients with CRS with nasal polyps, classifying nearly all such patients as Type 2 because of differences in baseline biomarker distributions. We discuss histological thresholds for defining ECRS and highlight that Asian studies support higher tissue eosinophil cut-offs, approximately 70 eosinophils per high-power field (HPF) or around 10% of total inflammatory cells, compared with the 10 eosinophils per HPF recommended by Western guidelines. This review also evaluates outpatient-friendly scoring systems, such as Japanese Epidemiological Survey of Refractory Eosinophilic Chronic Rhinosinusitis (JESREC) and newly proposed Korean diagnostic criteria, as well as emerging machine-learning approaches for noninvasive prediction of ECRS. We conclude that clinicians in Asia should adopt regionally validated criteria that integrate histological, serological, and clinical parameters to accurately identify Type 2 CRS, optimize selection of biologic candidates, and improve prognostic counseling in this population.

KEY WORDS: Sinusitis; Chronic disease; Eosinophilia; Th2 cells; Asia; Eastern

INTRODUCTION

Chronic rhinosinusitis (CRS) is a heterogeneous inflammatory disease of the nasal and paranasal sinus mucosa, characterized by symptoms that persist for more than 12 weeks and substantial impairment in quality of life [1]. Traditionally, CRS has been classified as CRS with nasal polyps (CRSwNP) and CRS without nasal polyps (CRSsNP). However, this phenotypic classification does not adequately capture the underlying immunological heterogeneity of the disease. Over the past decade, endotype-based approaches have identified distinct inflammatory patterns, most notably Type 2 eosinophil-dominant disease and non–Type 2 non-eosinophilic disease.

Type 2 CRS is driven by cytokines such as interleukin (IL)-4, IL-5, and IL-13 and is associated with tissue and blood eosinophilia, elevated total and specific immunoglobulin E (IgE), and frequent comorbidity with asthma and aspirin-exacerbated respiratory disease (AERD). In contrast, non–Type 2 CRS is characterized by greater involvement of interferon-gamma (IFN-γ), IL-17, neutrophilic inflammation, and fibrosis and tends to be less responsive to corticosteroids [1–3]. Accurate identification of Type 2 CRS has become increasingly important with the advent of biologic therapies targeting IL-4/13, IL-5, and IgE, all of which require reliable indicators of Type 2 inflammation for appropriate patient selection.

Most biologic indications and many diagnostic thresholds for Type 2 CRS have been derived from Western cohorts, in which eosinophilic CRSwNP is highly prevalent and often regarded as the typical form of polyp disease [1]. In East Asia, however, the inflammatory landscape appears more complex. Data from Korea, Japan, and China suggest substantial proportions of non-eosinophilic and mixed inflammatory patterns, together with biomarker distributions that differ from those reported in Western populations [4–6].

It is also important to distinguish between Type 2 CRS and eosinophilic chronic rhinosinusitis (ECRS). Type 2 CRS is an immunological classification based on cytokine-driven inflammatory pathways, whereas ECRS is primarily a histological classification based on tissue eosinophil infiltration. Although these entities overlap substantially, they are not synonymous. This review therefore focuses on criteria for identifying Type 2 CRS in East Asian populations while recognizing the practical role of ECRS-based histological assessment.

Because direct cytokine profiling of IL-4, IL-5, and IL-13 is not routinely available in clinical practice, tissue eosinophilia remains the most practical and widely used surrogate marker of Type 2 inflammation. Accordingly, in evaluating diagnostic criteria, this review uses histological eosinophilia as the primary reference standard while acknowledging that it is an imperfect proxy for the broader spectrum of Type 2 immune activation.

This review provides a comprehensive synthesis of histological, clinical, radiological, and biomarker data from East Asian cohorts, together with a critical appraisal of Western criteria such as those proposed in European Position Paper on Rhinosinusitis and Nasal Polyps 2020 (EPOS 2020) [1]. On the basis of these data, we discuss how Type 2 CRS should be defined and identified in Asian patients, where Western thresholds may be insufficient, and how newer composite scoring systems may improve prognostic stratification and biologic candidate selection.

CRS ENDOTYPES AND THE CONCEPT OF TYPE 2 INFLAMMATION

Early studies of CRS endotypes showed that CRSsNP and CRSwNP differ not only in the presence of polyps but also in remodeling patterns and immune polarization [7,8]. CRSsNP often exhibits fibrosis, upregulation of transforming growth factor-beta (TGF-β), and a Th1-skewed inflammatory profile, whereas CRSwNP more commonly shows stromal edema, downregulation of TGF-β, and a relative deficiency of regulatory T cells in Western studies. Within CRSwNP, further stratification has identified a spectrum ranging from Type 2-dominant eosinophilic disease to non–Type 2 non-eosinophilic disease, each with distinct clinical behavior [2].

Cluster analyses based on inflammatory biomarkers have further refined this framework by defining multiple CRS clusters with distinct cytokine signatures, different proportions of CRSwNP versus CRSsNP, and varying prevalence of asthma [3]. Some clusters are characterized by strong IL-5 expression, elevated eosinophil cationic protein (ECP), and increased IgE levels, often accompanied by Staphylococcus aureus superantigen-specific IgE (SE-IgE). These clusters are enriched in patients with CRSwNP and asthma and represent a prototypical Type 2 endotype. By contrast, clusters dominated by myeloperoxidase, IL-8, IL-6, IFN-γ, and IL-17 demonstrate neutrophilic inflammation, lower rates of asthma comorbidity, and a higher proportion of CRSsNP [3].

Taken together, these findings support the view that Type 2 CRS is best defined by a combination of tissue and systemic markers rather than by phenotype alone. Endotypes driven by IL-5, with or without SE-IgE and a high IgE burden, are strongly associated with severe eosinophilia and comorbid asthma [9] and are therefore most relevant to currently available biologic targets. In contrast, endotypes characterized by IFN-γ and IL-17 are more typical of non–Type 2 or mixed inflammatory disease, which may respond differently to conventional treatment and may be less likely to benefit from IL-5 or IL-4/13 blockade.

EOSINOPHILIC VERSUS NON–EOSINOPHILIC CRS: CLINICAL AND HISTOLOGIC FEATURES

ECRS and non-ECRS differ in symptoms, endoscopic appearance, computed tomography (CT) patterns, blood biomarkers, treatment response, and recurrence risk (Table 1) [7,10]. In widely cited comparative analyses, ECRS is associated with early reduction or loss of smell, bilateral polyps with highly viscous secretions, and ethmoid-dominant opacification on CT imaging. By contrast, non-ECRS more often presents with mucopurulent discharge, polyps confined to the middle meatus, and maxillary-dominant involvement in the early stage. Peripheral blood eosinophilia and frequent comorbid asthma are characteristic of ECRS. In addition, macrolide therapy tends to be ineffective in ECRS, and postoperative recurrence rates are high in ECRS. In non-ECRS, asthma is less common, macrolide therapy is often beneficial, recurrence rates are lower, and the role of systemic corticosteroids at recurrence is less clearly established.

The histological differences between these subtypes also reflect their biological divergence. ECRS typically shows marked eosinophilic infiltration of the polyp stroma, accompanied by lymphocytes and prominent basement membrane thickening as a feature of remodeling. In contrast, non-ECRS demonstrates less eosinophilia, relatively greater lymphocytic infiltration, and increased nasal gland structures rather than the edematous pattern that characterizes eosinophilic disease. These structural distinctions mirror the differing cytokine milieus and help explain why ECRS is often more corticosteroid-responsive yet more prone to recurrence, whereas neutrophil-dominant disease may be comparatively steroid-resistant but more amenable to long-term macrolide therapy.

TISSUE EOSINOPHIL COUNTS AS A CRITERION FOR DISTINGUISHING ECRS

Systematic reviews and meta-analyses have evaluated the extent to which different tissue eosinophil cut-offs distinguish ECRS from non-ECRS and predict postoperative recurrence in CRS [11,12]. Across prospective and retrospective studies from multiple countries, the proposed thresholds have ranged from >5 eosinophils per high-power field (HPF) to >120 eosinophils per HPF, with substantial variation in recurrence definitions and follow-up duration (Table 2). Despite this heterogeneity, a consistent pattern has emerged: higher eosinophil thresholds generally provide greater specificity, although with reduced sensitivity.

Importantly, the optimal threshold appears to differ substantially between Western and Asian populations (Table 2). Western guidelines generally use a lower cut-off of 10 eosinophils per HPF to define ECRS. In contrast, studies from Asia have shown that higher thresholds, either >55–120 eosinophils per HPF or >10% of total inflammatory cells, provide better discrimination for predicting recurrence and identifying clinically meaningful Type 2 disease. This discrepancy underscores the need for region-specific criteria in Asian practice rather than direct adoption of Western definitions.

Pooled analyses of Western and Asian studies suggest that a threshold of >55 eosinophils per HPF offers a favorable balance between sensitivity and specificity, with a sensitivity of approximately 0.87, a specificity of approximately 0.97, and a high positive likelihood ratio for predicting recurrence in ECRS [12]. Lower thresholds, such as >10 eosinophils per HPF, are more sensitive but substantially less specific, whereas very high thresholds, such as >120 eosinophils per HPF, are highly specific but fail to identify many recurrent cases. On the basis of these data, McHugh et al. [12] recommended a threshold of >55 eosinophils per HPF for predicting recurrence risk in ECRS.

These findings have direct implications for how ECRS is defined histologically in East Asian populations. As shown in Table 2, the thresholds used across Asian studies vary considerably, ranging from 55 to 120 eosinophils per HPF when absolute counts are used and from 8% to 11% when eosinophils are expressed as a proportion of total inflammatory cells. This variation reflects the absence of a standardized criterion for tissue eosinophilia in Asian populations. Among the currently used approaches, the Japanese Epidemiological Survey of Refractory Eosinophilic Chronic Rhinosinusitis (JESREC) scoring system, which remains one of the most widely adopted classification tools in Asia, uses a threshold of >70 eosinophils per HPF to define ECRS. Compared with the Western cut-off of 10 eosinophils per HPF, this higher threshold may better distinguish patients at true risk of poor clinical outcomes from those with only incidental or low-grade tissue eosinophilia, particularly in populations where non-Type 2 CRS remains prevalent.

In East Asian populations, a tissue eosinophil proportion of at least 10% per HPF has been the most commonly used criterion for defining ECRS and has shown strong correlation with Type 2 inflammation [13–15]. In our institutional data, a tissue eosinophil proportion of 10% per HPF corresponded to approximately 65 eosinophils per HPF when expressed as an absolute count. Notably, receiver operating characteristic (ROC) analysis from our prior study showed that a threshold of at least 65 eosinophils per HPF, rather than at least 10 eosinophils per HPF, was optimal for identifying Type 2 inflammation, yielding 100% sensitivity and 98.5% specificity (area under the ROC curve [AUC]=0.997, p<0.001) [15]. This threshold closely aligns with the JESREC framework and has also shown good discriminatory value for predicting polyp recurrence [5,16,17]. Taken together, these findings suggest that a practical threshold of at least 70 eosinophils per HPF or at least 10% of inflammatory cells represents a clinically reasonable compromise, balancing sensitivity and specificity in populations in which non–Type 2 CRS remains prevalent.

Integrating such histological thresholds with clinical scoring systems and peripheral blood biomarkers may further improve patient stratification. A combined approach may support more informed decisions regarding postoperative surveillance intensity, escalation of topical corticosteroid therapy, and selection of candidates for biologic treatment.

EPOS 2020 TYPE 2 CRITERIA AND THEIR LIMITATIONS IN ASIAN CRSwNP

The EPOS 2020 guideline proposes simple criteria for identifying evidence of Type 2 inflammation in CRSwNP: total serum IgE of at least 100 IU/mL, blood eosinophil count of at least 250 cells/μL, or tissue eosinophilia of at least 10 eosinophils per HPF. In a Korean retrospective cohort of 207 patients with CRSwNP, these criteria were systematically evaluated against a histological definition of ECRS based on tissue eosinophils accounting for more than 10% of total inflammatory cells [15]. In that cohort, ECRS accounted for approximately 37% of patients and was associated with higher prevalence of asthma and AERD, higher serum IgE and blood eosinophil levels, higher JESREC scores, and significantly higher recurrence rates than non-ECRS.

When the EPOS Type 2 criteria were applied to this Korean cohort, 95% of patients met at least one of the three thresholds, effectively classifying nearly the entire cohort as Type 2. Although this approach yielded a sensitivity of 100% for ECRS, its specificity was only approximately 8%, with an AUC of 0.645, indicating poor overall discriminatory performance. In practical terms, the EPOS 2020 criteria were too permissive in this setting and failed to distinguish truly eosinophilic, high-risk disease from non-ECRS.

The individual EPOS components also showed important limitations. ROC analysis indicated that the EPOS-recommended threshold of at least 10 eosinophils per HPF was neither optimally sensitive nor optimally specific in this cohort. Blood eosinophil count and total IgE showed only modest discriminatory ability, and each performed better at thresholds different from those specified by EPOS 2020. These findings likely reflect underlying differences in the distribution of inflammatory endotypes and biomarkers between Korean patients with CRSwNP and the Western cohorts on which the EPOS 2020 criteria were based.

The authors therefore concluded that the EPOS 2020 Type 2 criteria are not appropriate for selecting biologic candidates among Korean patients with CRSwNP and that new, regionally validated standards are needed. This conclusion likely has broader relevance across East Asia, where similarly mixed inflammatory profiles and variable eosinophil distributions have also been reported.

A NEW COMPOSITE SCORING SYSTEM FOR TYPE 2 INFLAMMATION

To address the limitations of EPOS 2020 in the Korean setting, a new composite scoring system for Type 2 inflammation was proposed that combines serum IgE, blood eosinophil percentage, and tissue eosinophil counts [15]. In this system, a total IgE level of 100–200 IU/mL is assigned 1 point and >200 IU/mL is assigned 2 points, blood eosinophils of 5%–10% are assigned 1 point and >10% are assigned 2 points, and tissue eosinophils of 5%–10% are assigned 1 point and at least 10% are assigned 2 points. A total score of 3 or higher defines Type 2 inflammation.

ROC analysis showed that this composite score achieved an AUC of approximately 0.862 for identifying ECRS defined by tissue eosinophilia of more than 10% of total cells, with a sensitivity of approximately 78% and a specificity of approximately 76% at the cut-off of 3 points. Its performance clearly exceeded that of the EPOS criteria and was comparable to JESREC in this cohort. When the new score was applied, approximately 44% of patients were classified as Type 2 and 56% as non–Type 2, proportions that more closely matched the histological distribution of ECRS and non-ECRS than did the near-universal Type 2 classification generated by EPOS 2020.

Clinically, patients classified as Type 2 by this new score had significantly higher rates of asthma and AERD, higher serum IgE and blood eosinophil levels, higher JESREC scores, and higher recurrence rates than non–Type 2 patients, despite similar preoperative and postoperative 22-item Sinonasal Outcome Test (SNOT-22) scores and similar CT scores. Kaplan-Meier analyses further showed that both Type 2 classification according to the new score and marked tissue eosinophilia were associated with significantly worse polyp recurrence-free survival.

These findings suggest that a multiparameter scoring system based on routine blood tests and standard histology may identify clinically meaningful Type 2 inflammation in Korean CRSwNP more accurately than simple single-threshold criteria derived from Western guidelines. Although independent validation in additional Asian cohorts is still needed, this framework illustrates how regional data can be used to recalibrate Type 2 definitions for both prognostic counseling and biologic candidate selection.

JESREC AND OUTPATIENT ENDOTYPING WITHOUT HISTOLOGICAL EVALUATION

Although tissue eosinophil counts and the composite scoring system described above provide valuable diagnostic and prognostic information, their use in routine practice is limited by the requirement for histological evaluation, which in turn requires tissue biopsy or endoscopic sinus surgery. To address this limitation, the JESREC study conducted in Japan introduced a practical scoring system and algorithm for classifying CRS as non-ECRS or as mild, moderate, or severe ECRS on the basis of clinical, radiological, and blood eosinophil parameters [5]. The JESREC score assigns points for bilateral disease, the presence of nasal polyps, ethmoid-dominant CT opacification, and graded categories of peripheral blood eosinophils, with a total score of at least 11 indicating ECRS. Additional stratification incorporates comorbid asthma and nonsteroidal anti-inflammatory drug intolerance to define mild, moderate, and severe ECRS subgroups.

In the original JESREC cohort, a threshold of 11 points yielded a sensitivity of approximately 83% and a specificity of approximately 66% for identifying ECRS. Immunological validation showed that ECRS, particularly severe ECRS, was associated with higher IL-5 levels and distinct cytokine profiles compared with non-ECRS. Recurrence-free survival analyses also demonstrated progressively worse outcomes from non-ECRS to mild, moderate, and severe ECRS over several years after surgery, highlighting the prognostic usefulness of this classification system.

More recently, Lee et al. [18] proposed a novel outpatient-friendly scoring system specifically validated in a Korean cohort of 640 patients with CRS. This model incorporates three readily available parameters: blood eosinophil percentage, bilateral anterior ethmoid Lund-Mackay score, and the presence of nasal polyps on endoscopy. The score is calculated as blood eosinophil (%) + anterior ethmoid Lund-Mackay score + 2 (if a nasal polyp is present), with a total score of 7 or greater indicating ECRS. When compared with JESREC, EPOS 2020, and EUFOREA, this novel score demonstrated comparable or superior diagnostic accuracy, with an AUC of 0.753 in the estimation group and 0.729 in the validation group. Notably, its sensitivity ranged from 71% to 75% and its specificity ranged from 71% to 79%, suggesting that it may serve as a practical tool for identifying likely ECRS before surgery and without histopathological confirmation.

Taken together, JESREC and the Korean outpatient scoring system illustrate how simple clinical, radiological, and laboratory variables can be combined to approximate tissue endotyping when immediate histological assessment is not available. For Asian practice, a stepwise strategy that applies these tools at initial evaluation and then confirms inflammatory status histologically when surgery is performed may offer a practical compromise between diagnostic accuracy and clinical feasibility. Table 3 summarizes and compares the diagnostic performance of these criteria in Asian populations.

GEOGRAPHIC DIVERSITY OF ENDOTYPES AND IMPLICATIONS FOR BIOLOGICS

Comparative cluster analyses from multiple regions, including Western centers such as Chicago, Benelux, and Adelaide, as well as Asian centers such as Beijing and Chengdu, have highlighted striking geographic differences in CRS endotypes [19]. In many Western cohorts, CRSwNP is dominated by Type 2 endotypes, with a high proportion of patients showing elevated IL-5, IgE, and ECP and, consequently, a large fraction of patients classified overall as Type 2. In several Asian cohorts, however, non–Type 2 or untypable endotypes are more common, particularly in CRSwNP, and Type 1 or Type 3 patterns may predominate depending on local genetic and environmental influences [6,20].

These geographic differences have important implications for the application of Western biologic criteria, including those proposed by EPOS 2020 and EUFOREA 2019, to Asian patients. If nearly all patients with CRSwNP in a given Asian cohort meet EPOS Type 2 criteria, as shown in the Korean data, then those criteria have limited discriminatory value for selecting candidates for costly biologic therapies and may overestimate the true prevalence of Type 2-driven disease. In addition, the relative contribution of Type 2 inflammation to symptoms and polyp growth may vary across regions, which could in turn influence biologic response rates and cost-effectiveness.

The Korean analysis of EPOS 2020 therefore suggests that Asian centers should develop and validate their own Type 2 criteria using local distributions of tissue eosinophils, blood eosinophils, and IgE and calibrating those thresholds against clinically meaningful outcomes such as recurrence and asthma comorbidity. In Asian settings, indications for biologic therapy may need to emphasize not only generic Type 2 markers but also marked tissue eosinophilia, high composite scores, poor outcomes despite surgery and optimized topical therapy, and comorbid asthma or AERD. Such an approach is likely to identify a smaller but more clearly defined group of patients who may derive meaningful benefit from biologics in resource-constrained health care systems.

EMERGING TOOLS: PREDICTIVE MODELING AND MACHINE LEARNING

Recent advances in computational methods have expanded the possibility of identifying ECRS noninvasively before histopathological confirmation. Several studies have developed predictive models, including nomograms and machine-learning algorithms, to distinguish ECRS from non-ECRS using readily available clinical, laboratory, and radiological variables [21–23].

A recent systematic review of artificial intelligence for ECRS detection included seven studies encompassing 2,410 patients [24]. Across these studies, investigators used a range of machine-learning algorithms, including neural network-based models, decision trees, random forests, and support vector machines. The pooled analysis showed a sensitivity of 0.857 and a specificity of 0.850, with AUC values ranging from 0.824 to 0.956. Feature-importance analyses consistently identified blood eosinophil-related measures and radiological patterns, particularly ethmoid-dominant opacification, as the strongest contributors to model performance. These findings are consistent with traditional clinical observations and with the core components of established systems such as JESREC. Although these computational tools still require external validation across diverse Asian populations, they may eventually complement simpler scoring systems, particularly in centers with access to advanced analytic infrastructure.

PRACTICAL APPROACH TO IDENTIFYING TYPE 2 CRS IN ASIAN PRACTICE

Taken together, the evidence reviewed here supports a practical stepwise approach for identifying Type 2 CRS in Asian clinical settings while accounting for regional endotype distributions. Fig. 1 illustrates this proposed algorithm. At the initial evaluation, all patients with CRS should first be phenotyped as CRSwNP or CRSsNP on the basis of symptoms and endoscopic findings. They should also be assessed for comorbid asthma, AERD, allergy, and severe olfactory loss. In patients with CRSwNP or severe disease, basic investigations, including CT imaging, peripheral blood eosinophil count, and total IgE, should be obtained to estimate the likelihood of Type 2 inflammation.

For patients proceeding to surgery, standardized histological assessment of polyp or ethmoid tissue should be performed, including both eosinophil counts per HPF and eosinophil percentage among inflammatory cells. Thresholds such as >70 eosinophils per HPF or >10% eosinophils may then be used to identify high-risk ECRS. At the same time, scoring systems such as JESREC and the Korean Type 2 score can be calculated to classify patients as non-ECRS, mild ECRS, moderate ECRS, severe ECRS, or Type 2 versus non–Type 2.

Patients classified as having Type 2 CRS or ECRS, marked tissue eosinophilia, and high clinical scores should be counseled regarding their increased risk of recurrence and comorbid asthma. They should also be considered for intensified postoperative topical therapy, careful long-term follow-up, and, when available and feasible, biologic therapy if symptoms remain uncontrolled despite optimal standard care. By contrast, patients with non–Type 2 disease may be managed with greater emphasis on macrolide therapy, infection and inflammation control, and judicious corticosteroid use, with biologic therapy reserved for those who later develop clear Type 2 features.

LIMITATIONS

This review has several limitations. Most validation data for Asian-specific diagnostic criteria have been derived from Korean, Japanese, and Chinese cohorts, and it remains uncertain whether these thresholds are directly applicable to other Asian populations, including those in Southeast Asia and India. Differences in environmental exposures, genetic backgrounds, and health care systems may all influence endotype distribution and biomarker cut-offs. In addition, prospective studies directly comparing the ability of different scoring systems to predict biologic treatment response in Asian patients are still lacking. Future multicenter studies across a broader range of Asian countries are therefore needed to validate and refine these approaches.

CONCLUSION

Accurate identification of Type 2 CRS and ECRS is central to prognosis and to the rational use of biologic therapies, yet criteria developed in Western populations cannot be directly applied to Asian practice without modification. Data from Korea and Japan show that non-eosinophilic and mixed inflammatory endotypes remain common, that marked tissue eosinophilia is a major determinant of recurrence, and that the simple EPOS 2020 Type 2 thresholds classify nearly all CRSwNP cases as Type 2, resulting in poor specificity. Histological eosinophil quantification, composite scores integrating blood eosinophils and IgE, and outpatient tools such as JESREC appear to offer more accurate and regionally appropriate approaches for defining Type 2 CRS in Asia.

Future work should focus on harmonizing and validating these criteria across Asian countries, linking them more directly to biologic outcomes, and incorporating emerging machine-learning models into practical clinical algorithms. By aligning endotyping strategies with local epidemiology and biomarker distributions, clinicians in Asia may be able to select biologic candidates more precisely, improve prognostic counseling, and ultimately provide more personalized care for patients with CRS.

Notes

Ethics Statement

Not applicable

Availability of Data and Material

Data sharing not applicable to this article as no datasets were generated or analyzed during the study.

Conflicts of Interest

The authors have no potential conflicts of interest to disclose.

Author Contributions

Conceptualization: Ji-Hun Mo, Shin Hyuk Yoo. Data curation: Shin Hyuk Yoo, Ki-Il Lee, Gwanghui Ryu. Formal analysis: Jun-Sang Bae, Shin Hyuk Yoo. Funding acquisition: Ji-Hun Mo. Investigation: Shin Hyuk Yoo, Ki-Il Lee, Gwanghui Ryu. Methodology: Jun-Sang Bae, Ji-Hun Mo. Project administration: Ji-Hun Mo. Resources: Ji-Hun Mo. Software: Jun-Sang Bae. Supervision: Ji-Hun Mo. Validation: Gwanghui Ryu, Jun-Sang Bae. Visualization: Shin Hyuk Yoo, Ki-Il Lee. Writing—original draft: Shin Hyuk Yoo, Ki-Il Lee, Gwanghui Ryu. Writing—review & editing: Ji-Hun Mo, Jun-Sang Bae.

Funding Statement

This research was supported by the Bio&Medical Technology Development Program (RS-2023-00220408) and the Basic Science Research Program (RS-2025-00554060, RS-2020-NR049585, RS-2022-NR075747) through the National Research Foundation of Korea (NRF), funded by the Korean government (MSIT and Ministry of Education).

Acknowledgments

None

Fig. 1

Practical approach for identifying Type 2 CRS in East Asian patients. CRS, chronic rhinosinusitis; CRSsNP, CRS without nasal polyps; CRSwNP, CRS with nasal polyps; AERD, aspirin-exacerbated respiratory disease; CT, computed tomography; IgE, immunoglobulin E; JESREC, Japanese Epidemiological Survey of Refractory Eosinophilic Chronic Rhinosinusitis; ECRS, eosinophilic chronic rhinosinusitis; eos, eosinophils; LM, Lund-Mackay; HPF, high-power field.

Table 1

Clinical and histological features distinguishing ECRS from non-ECRS

	ECRS	Non-ECRS
Characteristic symptoms	Reduction/loss of smell in early stages	Typical nasal/sinus symptoms
Endonasal findings	Bilateral polyps, high viscous secretion	Mucopurulent discharge, nasal polyp in middle meatus
Computed tomography findings	Ethmoid predominance (in early stages)	Maxillary predominance (in early stages)
Blood examination	Eosinophilia	-
Coexistence of asthma	Frequent	Less frequent
Macrolide therapy	Not effective	Effective
Recurrence rate of nasal polyps	Very high	low
Systemic steroid for recurrence	Higher efficacy	Unclear efficacy
Histology of nasal polyps	Eosinophilic, lymphocyte infiltration, basement membrane thickening (remodeling)	Lymphocyte infiltration, neutrophilic infiltration, glandular hyperplasia

Adapted from Ishitoya et al. Allergol Int 2010;59(3):239–45 [7], under the terms of the Creative Commons license. ECRS, eosinophilic chronic rhinosinusitis; non-ECRS, non-eosinophilic chronic rhinosinusitis.

Table 2

Tissue eosinophil cut-off criteria for defining eosinophilic CRS across different studies

Author	Country	Study design	Cut-off criteria	Reason/method for cut-off
Kountakis 2004 [25]	USA	Prospective	>5 eos/HPF	EG2 stained tissue
Vlaminck 2014 [26]	Belgium	Prospective	>5 eos/HPF	Based on Soler 2019 [27]
Brescia 2015 [28]	Italy	Prospective	>10 eos/HPF	No specific reason provided
Brescia 2016 [29]	Italy	Prospective	>10 eos/HPF	No specific reason provided
Do 2016 [30]	Australia	Prospective	>10 eos/HPF	Based on Snidvongs 2013 [31]
Soler 2010 [32]	USA	Prospective	≥10 eos/HPF	Disease-specific QOL improvement
Lou 2015 [33]	China	Retrospective	>55 eos/HPF	ROC curve (polyp recurrence)
Yamada 2019 [34]	Japan	Prospective	≥55 eos/HPF	ROC curve (CRS recurrence)
Jiang 2011 [35]	China	Prospective	>8% of inflammatory cells	2x SD of the mean of controls
Nakayama 2011 [16]	Japan	Prospective	≥70 eos/HPF	ROC curve (polyp recurrence)
Nakayama 2016 [17]	Japan	Retrospective	≥70 eos/HPF	Based on Nakayama 2011 [16]
Tokunaga 2015 [5]	Japan	Retrospective	≥70 eos/HPF	ROC curve (polyp recurrence)
Cao 2009 [13]	China	Prospective	>10% of inflammatory cells	2x SD of the mean of controls
Gao 2016 [14]	China	Prospective	>10% of inflammatory cells	Median proportion of eosinophils
Yoo 2023 [15]	South Korea	Retrospective	>10% of inflammatory cells	ROC curve (polyp recurrence)
Jeong 2011 [36]	South Korea	Prospective	>11% of inflammatory cells	Asthma and allergy / ROC curve
Nakayama 2012 [37]	Japan	Retrospective	≥80.5 eos/HPF	Cluster analysis
Ikeda 2013 [38]	Japan	Prospective	>100 eos/HPF	ROC curve (polyp recurrence)
Matsuwaki 2008 [39]	Japan	Retrospective	>120 eos/HPF	Highest OR for recurrence
Lou 2016 [40]	China	Retrospective	≥54.5% of inflammatory cells	Cluster analysis

ECRS, eosinophilic chronic rhinosinusitis; eos, eosinophils; HPF, high-power field; EG2, eosinophil granule protein 2; ROC, receiver operating characteristic; QOL, quality of life; SD, standard deviation; OR, odds ratio.

Table 3

Comparison of the diagnostic value of each set of criteria when applied to East Asian patients

	EPOS 2020 [1]	JESREC (Japan) [5]	Korean outpatient score [14]	Korean composite score [15]
Primary purpose	Identify Type 2 inflammation	Classify ECRS severity	Predict ECRS without histology	Identify Type 2 inflammation
Setting	Any	Outpatient/pre-surgical	Outpatient/pre-surgical	Post-surgical (requires histology)
Tissue eosinophil	≥10 eos/HPF	≥70 eos/HPF (for confirmation)	Not included	5%–10%/HPF: 1 point, ≥10%/HPF: 2 points
Blood eosinophil	≥250 cells/μL	≥2% to <5%: 4 points, ≥5% to <10%: 8 points, ≥10%: 12 points	Included as continuous variable (%)	5%–10%: 1 point, ≥10%: 2 points
Serum IgE	≥100 IU/mL	Not included	Not included	≥100 to <200 IU/mL: 1 point, ≥200 IU/mL: 2 points
CT findings	Not included	Ethmoid dominance: 2 points	Bilateral anterior ethmoid LM score	Not included
Clinical features	Not included	Bilateral disease: 3 points, Nasal polyps: 2 points, Asthma/NSAID intolerance (for severity grading)	Nasal polyps: 2 points	Not included
Scoring formula	Any 1 of 3 criteria positive	Sum of points	Blood eos (%) + Bilateral anterior ethmoid LM score + 2 (if nasal polyp present)	Sum of IgE + Blood eos + Tissue eos points
Cut-off for ECRS or Type 2 CRS	Any criterion met	≥11 points	≥7 points	≥3 points
Sensitivity	100%*	83%	71%–75%	78%
Specificity	8%*	66%	71%–79%	76%
AUC	0.645*	Not reported	0.729–0.753	0.862
Strengths	Simple, widely known	Validated in Japan, grades severity (mild/mod/severe)	No histology needed, outpatient-friendly	Best discrimination for ECRS, integrates multiple biomarkers
Limitations	Poor specificity in Asian populations	Requires multiple clinical parameters	Requires validation outside Korea	Requires surgical tissue

^* the sensitivity, specificity, and AUC data were derived from Korean cohort [13].

EPOS, European Position Paper on Rhinosinusitis and Nasal Polyps; JESREC, Japanese Epidemiological Survey of Refractory Eosinophilic Chronic Rhinosinusitis; ECRS, eosinophilic chronic rhinosinusitis; eos, eosinophils; CRS, chronic rhinosinusitis; HPF, high-power field; IgE, immunoglobulin E; CT, computed tomography; LM, Lund-Mackay; NSAID, nonsteroidal anti-inflammatory drug; AUC, area under the curve.

REFERENCES

1) Fokkens WJ, Lund VJ, Hopkins C, Hellings PW, Kern R, Reitsma S, et al. European position paper on rhinosinusitis and nasal polyps 2020. Rhinology 2020;58(Suppl S29):1–464.

2) Bachert C, Marple B, Schlosser RJ, Hopkins C, Schleimer RP, Lambrecht BN, et al. Adult chronic rhinosinusitis. Nat Rev Dis Primers 2020;6(1):86.

3) Tomassen P, Vandeplas G, Van Zele T, Cardell LO, Arebro J, Olze H, et al. Inflammatory endotypes of chronic rhinosinusitis based on cluster analysis of biomarkers. J Allergy Clin Immunol 2016;137(5):1449–56E4.

4) Kim DH, Kim SW, Basurrah MA, Hwang SH. Clinical and laboratory features of various criteria of eosinophilic chronic rhinosinusitis: a systematic review and meta-analysis. Clin Exp Otorhinolaryngol 2022;15(3):230–46.

5) Tokunaga T, Sakashita M, Haruna T, Asaka D, Takeno S, Ikeda H, et al. Novel scoring system and algorithm for classifying chronic rhinosinusitis: the JESREC study. Allergy 2015;70(8):995–1003.

6) Min JY, Kim JY, Sung CM, Kim ST, Cho HJ, Mun SJ, et al. Inflammatory endotypes of chronic rhinosinusitis in the Korean population: distinct expression of type 3 inflammation. Allergy Asthma Immunol Res 2023;15(4):437–50.

7) Ishitoya J, Sakuma Y, Tsukuda M. Eosinophilic chronic rhinosinusitis in Japan. Allergol Int 2010;59(3):239–45.

8) Zhang N, Van Zele T, Perez-Novo C, Van Bruaene N, Holtappels G, DeRuyck N, et al. Different types of T-effector cells orchestrate mucosal inflammation in chronic sinus disease. J Allergy Clin Immunol 2008;122(5):961–8.

9) Bachert C, Pawankar R, Zhang L, Bunnag C, Fokkens WJ, Hamilos DL, et al. ICON: chronic rhinosinusitis. World Allergy Organ J 2014;7(1):25.

10) Fujieda S, Imoto Y, Kato Y, Ninomiya T, Tokunaga T, Tsutsumiuchi T, et al. Eosinophilic chronic rhinosinusitis. Allergol Int 2019;68(4):403–12.

11) Toro MDC, Antonio MA, Alves Dos Reis MG, de Assumpcao MS, Sakano E. Achieving the best method to classify eosinophilic chronic rhinosinusitis: a systematic review. Rhinology 2021;59(4):330–9.

12) McHugh T, Snidvongs K, Xie M, Banglawala S, Sommer D. High tissue eosinophilia as a marker to predict recurrence for eosinophilic chronic rhinosinusitis: a systematic review and meta-analysis. Int Forum Allergy Rhinol 2018;8(12):1421–9.

13) Cao PP, Li HB, Wang BF, Wang SB, You XJ, Cui YH, et al. Distinct immunopathologic characteristics of various types of chronic rhinosinusitis in adult Chinese. J Allergy Clin Immunol 2009;124(3):478–84E2.

14) Gao T, Ng CL, Li C, Li YY, Duan C, Shen L, et al. Smoking is an independent association of squamous metaplasia in Chinese nasal polyps. Int Forum Allergy Rhinol 2016;6(1):66–74.

15) Yoo SH, Kim YA, Mo JH. Can EPOS2020 criteria of type 2 inflammation be applied to Asian patients with chronic rhinosinusitis? Acta Otolaryngol 2023;143(9):789–95.

16) Nakayama T, Yoshikawa M, Asaka D, Okushi T, Matsuwaki Y, Otori N, et al. Mucosal eosinophilia and recurrence of nasal polyps - new classification of chronic rhinosinusitis. Rhinology 2011;49(4):392–6.

17) Nakayama T, Asaka D, Kanaya H, Kuboki A, Haruna S. Prognostic factors for recurrence after endoscopic sinus surgery for chronic rhinosinusitis with nasal polyps. Auris Nasus Larynx 2016;43(6):641–7.

18) Lee JY, Kim DH, Kim SW, Im YH, Park CS, Kim DH, et al. Diagnostic criteria for eosinophilic chronic rhinosinusitis: comparative analysis and novel scoring system. Int Forum Allergy Rhinol 2024;14(11):1746–56.

19) Staudacher AG, Peters AT, Kato A, Stevens WW. Use of endotypes, phenotypes, and inflammatory markers to guide treatment decisions in chronic rhinosinusitis. Ann Allergy Asthma Immunol 2020;124(4):318–25.

20) Wang X, Zhang N, Bo M, Holtappels G, Zheng M, Lou H, et al. Diversity of TH cytokine profiles in patients with chronic rhinosinusitis: a multicenter study in Europe, Asia, and Oceania. J Allergy Clin Immunol 2016;138(5):1344–53.

21) Hua HL, Li S, Xu Y, Chen SM, Kong YG, Yang R, et al. Differentiation of eosinophilic and non-eosinophilic chronic rhinosinusitis on preoperative computed tomography using deep learning. Clin Otolaryngol 2023;48(2):330–8.

22) Zhou H, Fan W, Qin D, Liu P, Gao Z, Lv H, et al. Development, validation and comparison of artificial neural network and logistic regression models predicting eosinophilic chronic rhinosinusitis with nasal polyps. Allergy Asthma Immunol Res 2023;15(1):67–82.

23) Xiong P, Chen J, Zhang Y, Shu L, Shen Y, Gu Y, et al. Predictive modeling for eosinophilic chronic rhinosinusitis: nomogram and four machine learning approaches. iScience 2024;27(2):108928.

24) Rajan J, Rosen R, Karasik D, Richter J, Cabrera C, D’Anza B, et al. A preliminary review of the utility of artificial intelligence to detect eosinophilic chronic rhinosinusitis. Int Forum Allergy Rhinol 2025;15(2):203–7.

25) Kountakis SE, Arango P, Bradley D, Wade ZK, Borish L. Molecular and cellular staging for the severity of chronic rhinosinusitis. Laryngoscope 2004;114(11):1895–905.

26) Vlaminck S, Vauterin T, Hellings PW, Jorissen M, Acke F, Van Cauwenberge P, et al. The importance of local eosinophilia in the surgical outcome of chronic rhinosinusitis: a 3-year prospective observational study. Am J Rhinol Allergy 2014;28(3):260–4.

27) Soler ZM, Sauer DA, Mace J, Smith TL. Relationship between clinical measures and histopathologic findings in chronic rhinosinusitis. Otolaryngol Head Neck Surg 2009;141(4):454–61.

28) Brescia G, Marioni G, Franchella S, Ramacciotti G, Velardita C, Giacomelli L, et al. Can a panel of clinical, laboratory, and pathological variables pinpoint patients with sinonasal polyposis at higher risk of recurrence after surgery? Am J Otolaryngol 2015;36(4):554–8.

29) Brescia G, Marioni G, Franchella S, Ramacciotti G, Giacomelli L, Marino F, et al. A prospective investigation of predictive parameters for post-surgical recurrences in sinonasal polyposis. Eur Arch Otorhinolaryngol 2016;273(3):655–60.

30) Do TQ, Barham HP, Earls P, Sacks R, Christensen JM, Rimmer J, et al. Clinical implications of mucosal remodeling from chronic rhinosinusitis. Int Forum Allergy Rhinol 2016;6(8):835–40.

31) Snidvongs K, Chin D, Sacks R, Earls P, Harvey RJ. Eosinophilic rhinosinusitis is not a disease of ostiomeatal occlusion. Laryngoscope 2013;123(5):1070–4.

32) Soler ZM, Sauer D, Mace J, Smith TL. Impact of mucosal eosinophilia and nasal polyposis on quality-of-life outcomes after sinus surgery. Otolaryngol Head Neck Surg 2010;142(1):64–71.

33) Lou H, Meng Y, Piao Y, Wang C, Zhang L, Bachert C. Predictive significance of tissue eosinophilia for nasal polyp recurrence in the Chinese population. Am J Rhinol Allergy 2015;29(5):350–6.

34) Yamada T, Miyabe Y, Ueki S, Fujieda S, Tokunaga T, Sakashita M, et al. Eotaxin-3 as a plasma biomarker for mucosal eosinophil infiltration in chronic rhinosinusitis. Front Immunol 2019;10:74.

35) Jiang XD, Li GY, Li L, Dong Z, Zhu DD. The characterization of IL-17A expression in patients with chronic rhinosinusitis with nasal polyps. Am J Rhinol Allergy 2011;25(5):e171–5.

36) Jeong WJ, Lee CH, Cho SH, Rhee CS. Eosinophilic allergic polyp: a clinically oriented concept of nasal polyp. Otolaryngol Head Neck Surg 2011;144(2):241–6.

37) Nakayama T, Asaka D, Yoshikawa M, Okushi T, Matsuwaki Y, Moriyama H, et al. Identification of chronic rhinosinusitis phenotypes using cluster analysis. Am J Rhinol Allergy 2012;26(3):172–6.

38) Ikeda K, Shiozawa A, Ono N, Kusunoki T, Hirotsu M, Homma H, et al. Subclassification of chronic rhinosinusitis with nasal polyp based on eosinophil and neutrophil. Laryngoscope 2013;123(11):E1–9.

39) Matsuwaki Y, Ookushi T, Asaka D, Mori E, Nakajima T, Yoshida T, et al. Chronic rhinosinusitis: risk factors for the recurrence of chronic rhinosinusitis based on 5-year follow-up after endoscopic sinus surgery. Int Arch Allergy Immunol 2008;146(Suppl 1):77–81.

40) Lou H, Meng Y, Piao Y, Zhang N, Bachert C, Wang C, et al. Cellular phenotyping of chronic rhinosinusitis with nasal polyps. Rhinology 2016;54(2):150–9.