Characterization of uncontrolled, severe asthma patients with type 2 inflammation (T2): results from a physician survey across countries from Latin American, Eurasian Middle East regions and China

ABSTRACT

Objective

The 2019 GINA guidance incorporates the presence of T2 inflammation in severe asthma patients to determine eligibility for add-on biologic therapy, though little data exists to characterize this population. The objective of this manuscript is to conduct a descriptive analysis to characterize patients with severe asthma in emerging countries based on disease severity, patient exacerbation history, and T2 phenotype.

Methods

A cross-sectional survey of physicians treating asthma patients ages 12 years and older was conducted in eight countries. Physicians characterized their severe asthma patients and reported data from their patients’ medical charts. Medical chart data was selected from the physicians’ six most recent asthma patients taking prescription medication.

Results

A total of 550 physicians completed the survey and filled out 3,300 patient record forms. A total of 876 patients have been characterized with uncontrolled severe asthma. Of the 420 patients with available EOS lab data, 40% are indicated with T2 inflammation (EOS ≥150/µL). Ninety-one percent of all patients with available IgE lab data (n = 498) had IgE 30 − 1500 IU/mL indicating allergy-driven asthma. Finally, chronic OCS use (as reported by physicians) was reported in 11% of patients.

Conclusion

This research revealed that 65% of patients had at least one of three T2 inflammation comorbidities assessed: allergic rhinitis, chronic rhinosinusitis with nasal polyps, and atopic dermatitis. Discrepancies were observed between patients’ treatment regimens and GINA step reported, suggesting there may be room to improve understanding of asthma severity as defined per GINA guidelines as well as asthma control assessment in clinical practice.

Keywords:

• Severe asthma
• type 2 inflammation
• biomarkers
• EOS
• FeNO
• IgE
• comorbidities
• IL4 IL13
• Latin America
• Middle East
• China

Introduction

Asthma is a heterogeneous, chronic inflammatory disease characterized by airway inflammation and a history of respiratory symptoms including wheezing, shortness of breath, chest tightness, and/or coughing that vary over time, with potential lung function impairment (1). The cause of asthma is not fully understood; it is driven by a complex mix of genetic and environmental factors (1).

According to the 2019 GINA guidelines, asthma severity is evaluated retrospectively from the level of treatment required to control symptoms and can be assessed after patients have been on controller medication for several months.

Severe asthma is recognized as a specific asthma phenotype rather than an extreme manifestation of more common asthma variants (2). GINA guidelines include definitions for uncontrolled, difficult-to-treat, and severe asthma that are all interconnected. Uncontrolled asthma is characterized by poor symptom control and/or frequent or severe exacerbations. Difficult-to-treat asthma is uncontrolled despite the use of medium or high dose ICS with a second controller, or maintenance OCS, or requires these treatments to maintain control and reduce exacerbation risk. Severe asthma is a subset of difficult-to-treat asthma that is uncontrolled despite adherence with maximal optimized therapy and contributory factors (such as incorrect inhaler technic or comorbidities) have been addressed. Patients whose condition worsened when maximal treatment is decreased are also characterized as having severe asthma.

T2 inflammation as a driver of asthma

Research has illuminated the role of type 2 (T2) inflammation in the etiology and pathogenesis of asthma, which opens up the potential for its use to classify asthma severity (3,4). According to studies in patients with non-specified types of asthma (5), mild to moderate asthma (6), uncontrolled asthma (7), and severe asthma (8,9), around 50–70% of asthma patients have type 2 inflammation (8,9).

T2 inflammation is driven by both the innate and the adaptive arms of the immune system. Cells in the adaptive arm (Th0 and Th2 cells) and the innate arm (ILC2 cells, mast cells, and basophils) produce the pro-inflammatory type 2 cytokines IL-4, IL-13, and IL-5, which drive type 2 inflammation (4,10–12). These three cytokine mediators have overlapping roles (12):

• IL-4 initiates T-cell differentiation toward the Th2 subtype and induces production of type 2-associated cytokines, such as IL-4, IL-13, and IL-5—this creates a positive feedback loop

• IL-4 and IL-13 mediate B-cell activation, isotype switching and IgE production. They also play a role in fibrosis, airway remodeling, epithelial barrier dysfunction, FeNO production (13,14), and in eosinophil (EOS) trafficking to sites of inflammation

• IL-13 mediates goblet cell hyperplasia, airway smooth muscle contractility, and mucus over production

• IL-5 mediates EOS differentiation in the bone marrow, survival and mobilization, and migration from bone marrow to the blood

Biomarkers of T2 inflammation

Type 2 inflammation in asthma is associated with a range of elevated biomarker levels. These elevated biomarkers, which include higher blood EOS, higher serum IgE levels, and/or higher exhaled nitric oxide (FeNO) levels, are key clinical indicators of type 2 inflammation (1,8).

Biomarker data can further define T2 asthma. Specifically, elevated IgE is indicative of allergic asthma when asthma symptoms are driven by allergen exposure, while elevated IgE and blood EOS is indicative of allergic/eosinophilic asthma (or type 2 asthma); additionally, elevated EOS and/or FeNO may indicate type 2 asthma.

The 2019 GINA guidance recognizes T2 inflammation and associated biomarkers. Specifically, GINA provides guidance for characterizing T2 inflammation in severe patients to determine eligibility for add-on biologic therapy; GINA defines T2 inflammation as (1):

• Blood EOS ≥150/μL and/or

• FeNO ≥20 ppb and/or

• Sputum EOS ≥2% and/or

• Asthma is clinically allergen-driven and/or

• Need for maintenance oral corticosteroids

T2 inflammation comorbidities

T2 inflammation is the pathophysiology behind several other conditions, some linked with more severe asthma and a greater burden of disease (see Table 1).

Table 1. T2 inflammation comorbidities.

T2 comorbidity	Characteristics	Links with asthma
Chronic rhinosinusitis with nasal polyps (CRSwNP)	Eosinophil-rich nasal polyps Chronic sinusitis Mucus production (12)	Associated with premorbid and concurrent asthma, (15) and more severe asthma, especially in patients with nasal polyps; (1) appears to be driven by the IL-4/IL-13 pathway also associated with asthma and atopic dermatitis (11)
Atopic dermatitis	Bright red, flat areas of skin with oozing or exudate changing into dull red or pink and dry, lichenified skin Impaired skin barrier Transepidermal water loss (13)	Common allergic disease associated with asthma; may be associated with systemic type 2 inflammation (13)
Allergic rhinitis and rhinosinusitis	Sneezing, rhinorrhea, and nasal obstruction Postnasal drip, cough, irritability, and fatigue (16)	Patients with uncontrolled, persistent asthma are more susceptible to these conditions (17)

Asthma exacerbations are more likely in people with comorbid T2 inflammatory disease, and especially those with severe asthma and with upper airway comorbidities, such as rhinitis and chronic rhinosinusitis with nasal polyps (CRSwNP) (18,19).

In an analysis of 118,981 UK patients with actively-treated asthma (18), CRSwNP, rhinitis, and eczema were independent predictors of future asthma exacerbations.

The Severe Asthma Research Program (SARP) analyzes large cohorts of people to look into clinical phenotypes and molecular mechanisms of asthma (20). An analysis of 709 participants in the SARP-3 study (including 187 children) found chronic sinusitis was significantly associated with exacerbation frequency (19).

Although there is currently a lack of evidence—especially in emerging markets—on asthma patient profiling, awareness of the impact of T2 inflammation and managing the associated comorbidities could play a role in improving asthma control for many patients.

Study objectives

Based on the lack of evidence on asthma patient profiles in emerging markets, the objective of this manuscript is to characterize patients with severe asthma based on measures of disease severity, patient exacerbation history and phenotyping. Improved understanding of the different profiles of patients with severe T2 asthma could support personalized treatment approach.

The data reported here is a subanalysis related to uncontrolled severe asthma patients from a 2018 survey conducted among physicians treating asthma patients regardless of severity level across eight countries. The manuscript aims to develop point-in-time patient profiles to characterize severe asthma. Aspects of asthmatic patient profiles included exacerbation history, T2 inflammation biomarkers and T2 inflammation comorbidities to align with the current understanding of T2 asthma and the 2018 GINA guidance (the most recent version at the time of the survey).

Methods

A cross-sectional survey of physicians treating asthma patients ages 12 years and older was conducted in eight countries: Mexico (MEX), Brazil (BRA), Colombia (COL), Russia (RUS), Turkey (TUR), Saudi Arabia (KSA), United Arab Emirates (UAE), and China (CHN) during a period from June 6, 2018 to July 18, 2018. The physician sample size was selected to represent the population size of their respective countries. No statistical hypotheses was to be tested in this analysis, as the purpose of the study is to provide a descriptive analysis of the severe asthma population. The research was carried out in compliance with local codes of conduct for market research (21).

Survey design

The survey collected two types of information: declarative data reported from the physician perspective and data from patient medical charts, extracted and reported by the physicians.

First, physicians were asked to describe their asthma patient populations and treatment approaches for patients ages 12 years and older. This declarative portion of the survey included questions about the patient treatment regimens (including biologics, if applicable), GINA Step, control of asthma (pre- and post-physician exposure to the 2014 ERS/ATS definition), ambulance calls (Russia only), emergency room (ER) visits (all countries except Russia), hospitalizations, and T2 comorbidities. Physicians also provided their perspectives on treatment goals, patient OCS use, and considerations for biologic therapy.

Physicians were then instructed to complete patient record forms using medical chart data from a convenience sample of their six most recent asthma patients ages 12 years or older taking prescription medication regardless of the level of asthma severity, T2 inflammation profile or biomarkers. Physicians were asked to select 1–3 records for patients with uncontrolled asthma on a medium or high-dose ICS regimen, and the remaining records could be from any patient meeting the aforementioned criteria. Physicians were instructed to conduct data collection from their six most recent asthma patients without specification in order to avoid any selection bias. Specific information reported by physicians using patient medical charts is summarized in Table 2.

Table 2. Summary of main patient data reported by physicians.

Patient demographics	Age, gender
Patient health history	Comorbidities, especially atopic dermatitis, allergic rhinitis, and CRSwNP
Patient asthma history/status	Asthma age of onset, blood eosinophil (EOS) level ^a , Immunoglobulin E (IgE) levels ^a , FeNO measurement ^a , FEV1 % predicted ^a , # of exacerbations in the past 12 months, # of exacerbations requiring hospitalization in the past 12 months, # of ambulance calls in the previous year (Russia only), # of emergency room (ER) visits in the previous year (excluding Russia), GINA Step (based on the physician’s assessment) ^b
Treatment	Current treatment regimen, change in brand of biologic treatment (if applicable), treatment before biologic initiated (if applicable), OCS use before biologic initiated (if applicable), current OCS use, frequency of acute OCS use, duration of chronic OCS use, Asthma Control Test (ACT) or Asthma Control Questionnaire (ACQ) score, control on current treatment regimen

a Most recent test result was reported (prior to any biologic initiation, if applicable).

b Based on the physician’s assessment; physicians were exposed to the 2014 ERS/ATS definition in the declarative portion of the survey.

Table 3. Physician demographics.

Physician demographics	BRA (n = 70)	MEX (n = 71)	COL (n = 70)	RUS (n = 72)	UAE (n = 70)	KSA (N = 60)	TUR (n = 67)	CHN (n = 70)
Primary specialty (%)
Pulmonology	64	49	50	50	64	100	52	41
Allergy/allergology	36	51	36	50	14	–	48	30
Immunology	–	–	–	–	22	–	–	29
General practitioner/primary care	–	–	14	–	–	–	–	–
Gender (%)
Male	64	59	63	24	69	83	45	61
Female	36	41	37	76	31	17	55	39
Years in practice (mean, SD)	14.2 (6.6)	13.2 (6.7)	12.7 (7.9)	15.7 (7.1)	15.9 (7.0)	17.8 (7.5)	15.1 (7.5)	15.3 (5.9)
Practice setting (%)
Rural	1	–	1	–	N/A	N/A	3	7
Suburban	–	–	3	3	N/A	N/A	–	9
Urban	99	100	96	97	N/A	N/A	97	84
Number of asthma patients seen per month (mean, SD)	132 (99)	103 (98)	89 (74)	124 (120)	105 (96)	109 (76)	169 (120)	128 (88)
Average proportion of asthma patients seen by age group (%)
Asthma patients age 12–17	31	41	38	35	20	28	18	33
Asthma patients age 18+	69	59	62	65	80	72	82	67

Table 4. Patient demographics: uncontrolled, high-dose ICS (+ ≥1 controller) asthma patients age 12+.

Patient demographics	All (n = 876)	BRA (n = 118)	MEX (n = 135)	COL (n = 126)	RUS (n = 129)	UAE (n = 56)	KSA (n = 53)	TUR (n = 157)	CHN (n = 102)
Gender (%)
Male	43	37	51	40	55	45	53	52	54
Female	57	63	49	60	45	55	47	48	46
Age (mean, SD)	43 (19)	45 (17)	34 (17)	40 (18)	44 (21)	37 (12)	34 (14)	52 (15)	51 (21)
#, % of patients with ACT scores	n = 402 46%	n = 28, 24%	n = 72, 53%	n = 73, 58%	n = 62, 48%	n = 7, 13%	n = 5, 9%	n = 110, 70%	n = 45, 44%
ACT score (mean, SD)	16.5 (4.3)	15.0 (4.6)	16.9 (3.9)	15.5 (4.1)	16.5 (4.9)	20.4 (4.2)	14.2 (5.1)	17.1 (4.1)	16.2 (4.2)
#, % of patients with ACQ scores	n = 169 19%	n = 13, 11%	n = 13, 9.6%	n = 3, 2.3%	n = 41, 32%	n = 4, 7%	n = 1, 2%	n = 61, 39%	n = 33, 32%
ACQ score (mean, SD)	2.5 (1.5)	4.1 (1.2)	2.4 (1.8)	1.4 (2.2)	2.4 (1.3)	3.0 (0.8)	2.0 (0.0)	1.8 (1.0)	3.5 (1.4)
#, % of patients with FEV1 test values	n = 652 74%	n = 79, 67%	n = 98, 72%	n = 106, 84%	n = 108, 84%	n = 27, 48%	n = 16, 30%	n = 147, 94%	n = 71, 70%
FEV1 test value, % of predicted value (mean, SD)	63.0 (14.2)	59.3 (14.0)	66.5 (13.7)	68.2 (14.3)	57.4 (14.8)	62.0 (12.6)	58.0 (19.2)	63.0 (11.7)	64.6 (14.4)

Table 5. Asthma severity: uncontrolled, high-dose ICS (+ ≥1 controller) patients age 12+.

Asthma severity	All (n = 876)	BRA (n = 118)	MEX (n = 135)	COL (n = 126)	RUS (n = 129)	UAE (n = 56)	KSA (n = 53)	TUR (n = 157)	CHN (n = 102)
OCS use (%) ^a
Yes: chronic	11	7	14	10	11	9	17	17	5
Yes: acute	12	12	20	8	10	16	8	6	22
No	76	81	66	82	79	75	75	76	74
GINA step (physician-reported) (%) ^b
Step 1	1	–	–	1	2	2	2	–	4
Step 2	4	5	3	3	1	7	6	1	12
Step 3	22	22	23	18	30	36	15	17	21
Step 4	51	57	48	50	62	39	45	50	49
Step 5	21	16	26	28	5	16	32	31	15
Patients with Biologic add-on to current treatment (%)	15	4	19	22	6	11	2	14	24

a Based on physician’s assessment.

b GINA Step was physician-reported and based on the physician’s assessment, not on the treatment regimen.

Following GINA guidance regarding the importance of phenotyping patients with a confirmed diagnosis of severe asthma, this manuscript will focus on a subanalysis of the patient data for the subset of severe patients, defined as having uncontrolled asthma and receiving high-dose ICS plus at least one controller. The objective was to assess asthma severity (considering background therapy and GINA step), exacerbation history (including associated hospitalizations and ER visits/ambulance calls), and asthma phenotyping based on T2 inflammation biomarkers and comorbidities to provide a point-in-time characterization of severe asthma patients using real world evidence.

Survey participants

Participants were selected from a pool of pulmonologists, allergists, immunologists, and general practitioners. Each country physician sample was determined by local treatment patterns to ensure inclusion of physicians who routinely see, treat and manage asthma patients. Participating physicians had to spend at least 50% of their professional time performing direct patient care and see a minimum of 25 asthma patients age 12+ years per month with at least 50% of these patients being treated with prescription medication. Physicians were also required to have been practicing between 4 and 30 years. Physicians were excluded from participation if any member of their household was affiliated with a pharmaceutical manufacturer or if they were currently participating in a clinical trial as an investigator or patient.

Analysis

The analysis was conducted at the individual country and global level. Categorical variables were reported with the number and percentage of patients for each category. Continuous variables were reported with mean and standard deviation (SD).

Results

A total of 550 physicians completed the survey and filled out 3,300 patient record forms. Key findings were reported for the subset of patient record forms for uncontrolled asthma patients on high-dose ICS with at least one controller, which represented 27% (n = 876) of the overall cohort. Physician and patient demographics are reported in Table 3 and Table 4, respectively. Supplementary data tables provide further data on the uncontrolled, medium-dose ICS population, and the adult population only (ages 18 years and older).

Key Findings

Asthma severity

Overall, physicians reported that 11% of patients were considered to be chronic OCS users. In comparison, a higher proportion of patients in Turkey (17%) were deemed to be chronic OCS users (Table 5).

The majority of patients overall were classified by physicians as being on GINA Steps 4 or 5 (72%) which aligned with the current GINA guidance at the time of the survey (2018). Per GINA 2018, treatment with high-dose ICS alone or medium dose plus a second controller could be considered as GINA Step 3 or higher (22). However, physicians classified 5% of patients as being on GINA Steps 1 or 2 which indicated some discordance between physician-reported GINA Step and severity considering the current treatment regimen.

ACT and ACQ scores to assess more broadly the level of asthma control were reported in a limited number of patients, respectively, 46% and 19%. Overall patients had a poor level of asthma control with a mean ACT and ACQ score of 16.5 and 2.7, respectively.

Exacerbation history

The majority of overall patients (96%) had experienced at least one exacerbation regardless of severity in the past 12 months. Among these patients, the mean (SD) number of exacerbations experienced per patient over the past 12 months was 4.1 (4.8). Additionally, 76% of these patients had at least one exacerbation that required hospitalization, and the mean (SD) number of exacerbations requiring hospitalization per patient in the past 12 months (among patients who experienced at least one exacerbation) was 1.9 (2.5) (Table 6).

Notably, patients in Russia and China experienced a mean (SD) of 5.0 (6.0) and 6.6 (5.8) exacerbations respectively, which was greater than the global average. Moreover, Chinese patients experienced a greater mean (SD) number of exacerbations that required hospitalization [4.9 (4.4)].

Overall, 89% of patients required an ER visit at least once in the previous year and the mean (SD) ER visits per patient was 3.7 (4.8)ⁱ.

Russian and Chinese patients required a mean (SD) of 5.2 (5.7) and 6.3 (7.9) ER visits respectively, which were greater than the overall study population value.

Asthma phenotyping

Physicians extracted and reported their patients’ most recent biomarker test results when available in the medical charts; blood EOS level, FeNO measurement and IgE level was reported for 48%, 7%, and 57% of patients, respectively.

Overall, the mean (SD) EOS level among all patients who had available EOS test results was 203.0 (265.9) cells/µL; 40%, 31%, and 25% of patients had EOS ≥150, 300, and 400 cells/µL, respectively. Patients in Mexico and China had mean (SD) EOS levels of 376.2 (332.1) cells/µL and 459.3 (310.6) cells/µL, respectively, which were greater than the overall study population value. Additionally, higher proportions of patients in Brazil, Mexico, Colombia, and China were represented by some EOS subgroups as compared with overall data (see Table 7).

Table 7. Biomarker-based phenotypes: Uncontrolled, high-dose ICS (+ ≥1 controller) asthma patients age 12+.

Biomarker-based phenotypes	All (n = 876)	BRA (n = 118)	MEX (n = 135)	COL (n = 126)	RUS (n = 129)	UAE (n = 56)	KSA (n = 53)	TUR (n = 157)	CHN (n = 102)
#, % of patients with blood EOS lab data	n = 420, 48	n = 41, 35	n = 60, 44	n = 66, 52	n = 83, 64	n = 16, 29	n = 5, 9	n = 113, 72	n = 36, 35
EOS (cells/µL) (mean, SD)	203.0 (265.9)	222.4 (198.6)	376.2 (332.1)	236.9 (236.4)	107.6 (185.6)	154.2 (222.5)	179.0 (239.5)	80.7 (189.0)	459.3 (310.6)
EOS ≥150 cells/µL (%)	40	56	67	55	23	38	20	16	72
EOS ≥300 cells/µL (%)	31	37	60	33	20	19	20	12	67
EOS ≥400 cells/µL (%)	25	20	47	23	17	19	20	10	67
#, % of patients with FeNO lab data	n = 65, 7	n = 10, 8	n = 3. 2	n = 1, 1	n = 16, 12	n = 4, 7	n = 0, 0	n = 0, 0	n = 31, 31
FeNO (ppb) (mean, SD)	90.7 (52.3)	60.4 (8.8)	66.7 (30.6)	81.0 (0.0)	45.8 (30.6)	50.5 (23.6)	–	–	131.4 (43.1)
FeNO ≥20 ppb (%)	98	^a	^a	^a	^a	^a	–	–	97
FeNO ≥25 ppb (%)	95	^a	^a	^a	^a	^a	–	–	97
#, % of patients with IgE lab data	n = 498, 57	n = 53, 45	n = 91, 7	n = 79, 63	n = 92, 71	n = 17, 30	n = 11, 21	n = 120, 76	n = 35, 34
IgE (IU/mL) (mean, SD)	437.1 (730.6)	746.3 (1174.8)	625.8 (1122.6)	324.2 (386.8)	413.9 (377.3)	516.3 (516.3)	444.7 (350.2)	222.4 (517.0)	489.5 (302.2)
IgE 30 − 1500 IU/mL (%)	91	89	95	84	97	82	73	95	89
IgE >700 IU/mL (%)	5	2	11	5	–	6	–	6	14
#, % of patients with EOS or FeNO lab data	n = 426, 49	n = 41, 35	n = 62, 46	n = 66, 52	n = 86, 67	n = 17, 30	n = 5, 9	n = 113, 72	n = 36, 35
#,% of patients with both EOS and FeNO lab data	n = 59, 7	n = 10, 8	n = 1, 1	n = 1, 1	n = 13, 10	n = 3, 5	n = 0	n = 0	n = 31, 30
EOS <150 and FeNO ≥25 ppb (%)	54	^a	^a	^a	^a	^a	–	–	24
#, % of patients with EOS or IgE lab data	n = 545, 62	n = 58, 49	n = 103, 76	n = 86, 68	n = 104, 80	n = 23, 41	n = 11, 21	n = 122, 78	n = 38, 37
EOS ≥300 cells/µL or IgE 30 − 1500 IU/mL (%)	88	90	95	83	86	65	73	94	82

a Very limited sample size.

Mean (SD) FeNO measurement across all patients was 90.7 (52.3) ppb; 98% and 95% had FeNO of 20 and 25 ppb, respectively. Data at the country-level was limited, with the exception of China.

Levels of total IgE were assessed as a proxy for allergy-driven asthma. At the overall study population level, mean (SD) IgE was 437.1 (730.6) IU/mL; 91% of patients had IgE levels within the range of IgE 30 − 1500 IU/mL.

Additional data on biomarker subgroups are summarized in Table 7.

The majority of patients had at least one of three T2 inflammation comorbidities assessed (65%)—atopic dermatitis (AD), CRSwNP, allergic rhinitis (AR). Higher proportions of patients in Russia, Turkey, and China had no T2 comorbidities versus the overall study population (see Table 8 and Figure 1).

Figure 1. T2 inflammation comorbidities: Uncontrolled, high-dose ICS (+ >1 controller) patients age 12+. *AD = atopic dermatitis; CRSwNP = chronic rhinosinusitis with nasal polyps; AR = allergic rhinitis.

Table 8. T2 inflammation comorbidities: Uncontrolled, high-dose ICS (+ ≥1 controller) patients age 12+.

T2 inflammation comorbidities	All (n = 876)	BRA (n = 118)	MEX (n = 135)	COL (n = 126)	RUS (n = 129)	UAE (n = 56)	KSA (n = 53)	TUR (n = 157)	CHN (n = 102)
Do not have any T2 comorbidities (%)	35	25	22	26	43	21	26	55	43
Has AD; does not have CRSwNP or AR (%)	4	1	5	4	5	7	4	2	5
Has CRSwNP; does not have AD or AR (%)	4	1	2	3	8	4	6	4	7
Has AR; does not have AD or CRSwNP (%)	35	50	39	43	23	36	34	25	29
Has AD and CRSwNP; does not have AR (%)	1	–	–	1	–	2	–	1	2
Has AD and AR; does not have CRSwNP (%)	11	12	15	13	16	11	8	4	5
Has CRSwNP and AR; does not have AD (%)	8	7	12	8	2	11	21	6	9
Has AD, CRSwNP, and AR (%)	3	4	5	2	3	9	2	2	–

Discussion

This analysis sought to characterize uncontrolled, severe asthma patients age 12 years or older across eight countries considering GINA guidance outlining indicators of T2 inflammation. Physicians reported data from a convenience sample of their six most recent asthma patients ages 12 years or older taking prescription medication. While they were asked to include 1 to 3 patients on a medium or high-dose ICS regimen, selection was not based on the patient’s T2 inflammation profile or biomarkers. The subanalysis focusing only on severe asthma patients showed a high burden of factors associated with T2 inflammation. Specifically, according to the 2019 GINA guidance for recognizing potential T2 inflammation, many patients included in the survey with EOS lab data recorded (n = 420) can be classified as having T2 inflammation as 40% had EOS ≥150/µL. Among all patients with available FeNO lab data (n = 65), 98% had FeNO ≥20 ppb. With IgE data as proxy for allergy-driven asthma, 91% of all patients with available IgE lab data (n = 498) had IgE 30 − 1500 IU/mL. Finally, chronic use of OCS (used as a proxy for maintenance OCS) was reported in 11% of all patients included in the survey.

Chronic OCS treatment and treatment on biologics may have had an impact on biomarker levels; however, the purpose of this study was to look at all severe asthma patients being treated at a specific point in time, not look at the variation in biomarker levels over time with different treatments. Additionally, the respective populations of these treatment groups were low, as 11% of patients use chronic OCS, and 15% of patients use a biologic add on, limiting the potential impact of medications on the interpretation of biomarker levels.

Type 2 inflammation comorbidities such as allergic rhinitis (AR), CRSwNP and atopic dermatitis (AD) were observed in respectively 59% (36% AR only), 17% (4% CRSwNP only), and 20% (4% AD only) of the overall population. These findings are in line with current published data (23). Discordance between patient treatment regimen and physician-reported disease severity in terms of GINA Step was noted. This discrepancy indicates either a misinterpretation of asthma severity when using GINA Steps definitions as per treatment guidance versus physician interpretation of this guidance or an error in reporting.

There were a limited number of patients with reported data on asthma control using ACT or ACQ score, suggesting that assessment of level of control with these tools is limited in clinical practice or the data has not been reported.

Use of biologics was limited, ranging from 2% (KSA) to 24% (CHN). This could be due to limited access to biologics at the time of the study; omalizumab was available across all countries, while mepolizumab was available in four countries (MEX, RUS, UAE, and KSA) and reslizumab was only available in one country (RUS).

Limitations

There are limitations to this analysis that should be considered alongside the results. Patient data was reported by physicians who were instructed to extract data from medical charts as part of a survey and no confirmatory testing was conducted to validate these data. Also, comorbidities were physician or patient-reported and were not corroborated with claims data. Patient ACT/ACQ scores and biomarker lab values were reported for patients that had this information available in their medical records upon physician review and extraction. Additionally, data availability reflects real-life practice and variability in treatment guidelines. Furthermore, FEV1 tests were not always performed, which may have been impacted by a lack of facilities capable of performing spirometry in certain countries and regions. Biomarker data was also very limited for some countries; it is possible that blood EOS level testing, IgE level testing and FeNO measurement is not performed regularly for asthma patients in some countries. In particular, FeNO data was limited. The FeNO test is relatively new and lack of reimbursement may be a barrier to its adoption. Additionally, FeNO measurement was not included in the GINA guidance available at the time of the survey (2018); however, the most recent GINA guidance (2019) recommends the evaluation of FeNO as it can further support characterization of T2 inflammation and may also be a predictive factor of response to some T2 inflammation-targeted treatments. With regards to EOS testing, while parasitic infections such has helminthic infections, have a decreasing prevalence worldwide, it may have a significant presence in developing countries. These infections can stimulate Type 2 helper cells (Th2) immune response with up-regulation of cytokines IL-4-, IL-5-, and IL-13 mediated IgE and EOS (24). Where relevant, physicians may test for parasitic infection and treat if present before commencing type 2 targeted treatment (1).

Conclusions

The data provides an increased understanding of the different phenotypes and endotypes among severe, uncontrolled asthma patients with T2 inflammation. The increased understanding of severe asthma patient profiles can support the development of personalized treatment approaches. Characterization of T2 asthma has been specified in the 2019 GINA guidance and key indicators such as blood EOS, FeNO, allergen-driven asthma and OCS dependency should be considered. Multiple comorbidities related to T2 inflammation such as CRSwNP and moderate to severe atopic dermatitis should also be considered when determining eligibility for biologic add-on therapy as per the 2019 GINA guidance. This survey showed that 65% had at least one of three T2 inflammation comorbidities assessed (65%)—atopic dermatitis (AD), CRSwNP or Allergic rhinitis (AR). Use of biomarkers such as IgE or blood eosinophils are quite common, but FeNO data was limited despite its role to define type 2 asthma status. Discrepancies between treatment-defined asthma severity and physician perceived severity based on GINA classifications suggest there may be room to improve the understanding of asthma severity as defined per GINA Step definitions as well as asthma control assessment in clinical practice.

Disclosure statement

The authors wish to report the following conflicts of interest: Irina Kosoy and William Derrickson are paid consultants of Sanofi, sponsor of the research. Elisheva Lew is an employee of Sanofi, sponsor of the research. Olivier Ledanois is an employee of Sanofi, sponsor of the research.

Table 6. Exacerbation: uncontrolled, high-dose ICS (+ ≥1 controller) patients age 12+.

Exacerbation history	All (n = 876)	BRA (n = 118)	MEX (n = 135)	COL (n = 126)	RUS (n = 129)	UAE (n = 56)	KSA (n = 53)	TUR (n = 157)	CHN (n = 102)
# of exacerbations, past 12 months (%)
0	4	1	2	9	2	5	11	3	–
1+	96	99	98	91	98	95	89	97	100
2+	80	88	79	65	90	86	75	64	98
3+	58	58	53	45	74	68	57	43	83
4+	39	37	30	33	46	46	36	30	64
# of exacerbations, past 12 months (patients with at least one exacerbation) (mean, SD)	4.1 (4.8)	4.7 (7.2)	3.4 (3.1)	3.2 (3.3)	5.0 (6.0)	3.9 (3.2)	3.1 (2.1)	2.9 (2.7)	6.6 (5.8)
# of exacerbations requiring hospitalization (patients with at least one exacerbation), past 12 months (%)
0	24	43	33	30	12	26	36	14	4
1+	76	57	67	70	88	74	64	86	96
2+	42	30	33	35	56	34	30	36	79
3+	22	13	16	17	33	15	11	13	58
4+	13	9	7	9	17	4	4	7	45
# of exacerbations requiring hospitalization, past 12 months (patients with at least one exacerbation) (mean, SD)	1.9 (2.5)	1.4 (2.6)	1.3 (1.5)	1.5 (1.8)	2.2 (1.9)	1.4 (1.6)	1.2 (1.3)	1.5 (1.2)	4.9 (4.4)
# of ER visits in the previous year ^a (%)
0	11	9	13	17	12	14	28	4	1
1+	89	91	87	83	88	86	72	96	99
2+	68	75	56	60	74	73	49	64	88
3+	50	52	32	48	61	55	38	43	77
4+	36	35	21	37	50	34	28	26	57
# of ER visits in the previous year ^a (mean, SD)	3.7 (4.8)	3.6 (5.1)	2.5 (3.0)	2.9 (2.8)	5.2 (5.7)	3.4 (3.8)	2.6 (2.9)	3.1 (3.4)	6.3 (7.9)

a For Russia, Physicians reported the number of ambulance calls in the previous year per patient; in all other countries, physicians reported the # of ER visits in the previous year per patient, for all patients.

Table A4. Biomarker-based phenotypes: Uncontrolled, high-dose ICS (+ ≥1 controller) asthma patients age 18+.

Biomarker-based phenotypes	Global (n = 648)	BRA (n = 104)	MEX (n = 75)	COL (n = 79)	RUS (n = 92)	UAE (n = 48)	KSA (n = 46)	TUR (n = 131)	CHN (n = 73)
#, % of patients with blood EOS lab data	n = 298, 46	n = 37, 36	n = 35, 47	n = 34, 43	n = 58, 63	n = 12, 25	n = 4, 9	n = 90, 69	n = 28, 38
EOS (cells/µL) (mean, SD)	206.53 (264.1)	217.8 (200.8)	397.4 (325.2)	238.0 (234.8)	132.7 (199.2)	141.2 (170.9)	211.3 (263.7)	64.6 (157.6)	551.2 (274.2)
EOS ≥ 150 cells/µL (%)	41	64	71	59	29	42	25	13	82
EOS ≥ 300 cells/µL (%)	32	43	66	24	26	25	25	10	82
EOS ≥ 400 cells/µL (%)	25	27	49	15	21	17	25	8	82
#, % of patients with FeNO lab data	n = 49, 8	n = 10, 10	n = 0. 0	n = 0, 0	n = 10, 11	n = 3, 6	n = 0, 0	n = 0, 0	n = 26, 36
FeNO (ppb) (mean, SD)	101.2 (52.6)	60.4 (8.8)	–	–	50.5 (38.5)	54 (27.6)	–	–	141.9 (31.8)
FeNO ≥ 20 ppb (%)	100	100	–	–	100	100	–	–	100
FeNO ≥ 25 ppb (%)	96	100	–	–	80	100	–	–	100
#, % of patients with IgE lab data	n = 341, 53	n = 47, 45	n = 44, 59	n = 44, 56	n = 60, 65	n = 13, 27	n = 9, 20	n = 96, 73	n = 28, 38
IgE (IU/mL) (mean, SD)	406.0 (688.5)	745.5 (1231.6)	567.8 (916.9)	208.1 (218.7)	368.3 (338.1)	534.8 (587.1)	499 (353.7)	217.3 (531.3)	531 (268.1)
IgE 30 − 1500 IU/mL (%)	90	89	89	75	95	77	78	95	93
IgE > 700 IU/mL (%)	15	23	22	2	15	31	22	4	36
#,% of patients with both EOS and FeNO lab data	n = 45, 7	n = 10, 8	–	–	n = 7, 8	n = 2, 4	–	–	n = 23, 32
EOS < 150 and FeNO ≥ 25 ppb (%)	54	20	*	*	43	100	–	–	88

Table A5. T2 inflammation comorbidities: Uncontrolled, high-dose ICS (+ ≥1 controller) patients age 18+.

T2 inflammation comorbidities	Global (n = 876)	BRA (n = 118)	MEX (n = 135)	COL (n = 126)	RUS (n = 129)	UAE (n = 56)	KSA (n = 53)	TUR (n = 157)	CHN (n = 102)
Do not have any T2 comorbidities (%)	39	28	33	32	52	23	24	56	48
Has AD; does not have CRSwNP or AR (%)	3	1	4	4	5	6	4	2	7
Has CRSwNP; does not have AD or AR (%)	4	1	2	3	9	4	2	5	5
Has AR; does not have AD or CRSwNP (%)	33	50	32	42	25	38	35	24	26
Has AD and CRSwNP; does not have AR (%)	–	–	–	–	–	2	–	2	0
Has AD and AR; does not have CRSwNP (%)	7	9	8	10	4	8	9	3	7
Has CRSwNP and AR; does not have AD (%)	8	7	15	8	–	10	24	6	7
Has AD, CRsWNP and AR (%)	4	5	3	2	4	4	2	2	–

Additional information

Funding

Funding This work was funded by Sanofi and Regeneron.

Funding

Funding This work was funded by Sanofi and Regeneron.

Notes

i Russia reported ambulance calls due to exacerbations while all other countries reported emergency room visits due to exacerbations. For the sake of simplicity, this manuscript uses ambulance calls as a proxy for ER visits.

Appendix A

Table A1 Patient demographics: uncontrolled, high-dose ICS (+ ≥1 controller) asthma patients age 18+.

Patient demographics	Global (n = 648)	BRA (n = 104)	MEX (n = 75)	COL (n = 79)	RUS (n = 92)	UAE (n = 48)	KSA (n = 46)	TUR (n = 131)	CHN (n = 73)
Gender (%)
Male	48	48	46	43	47	46	58	52	59
Female	52	52	54	57	53	55	42	48	41
Age (mean, SD)	47 (16)	46 (15)	40 (14)	42 (15)	50 (15)	39 (12)	39 (12)	52 (15)	52 (19)
Patient satisfaction with treatment on a scale of 1 to 7 (1 = not at all satisfied; 7 = extremely satisfied) (%)
7	6	3	12	14	8	20	11	5	3
6	17	17	27	22	15	42	15	16	15
5	24	30	23	26	23	24	22	27	22
4	24	28	22	16	33	7	20	32	14
3	19	16	12	16	13	4	21	12	25
2	8	5	2	4	7	3	9	6	16
1	2	0	2	2	2	0	2	2	5
#, % of patients with ACT scores	n = 292 45	n = 23, 22	n = 41, 55	n = 46, 58	n = 44, 48	n = 6, 12	n = 4, 9	n = 92, 70	n = 36. 49
ACT score (mean, SD)	16.1 (4.2)	15.3 (4.7)	16.7 (3.4)	15.0 (4.1)	15.9 (5.0)	20.2 (4.6)	14.8 (5.7)	16.4 (4.1)	16.2 (4.1)
#, % of patients with ACQ scores	n = 129 20	n = 13, 12	n = 11, 12	n = 1, 1	n = 31, 34	n = 3, 6	n = 0, 0	n = 48, 37	n = 24, 33
ACQ score (mean, SD)	2.7 (1.4)	4.1 (1.2)	3.2 (1.6)	4 (0)	2.1 (1.2)	3.0 (1.0)	0 (0.0)	1.8 (1.0)	3.8 (1.1)
#, % of patients with FEV1 test values	n = 474 73	n = 67, 64	n = 56, 75	n = 67, 85	n = 78, 85	n = 23, 48	n = 14, 30	n = 122, 93	n = 47, 64
FEV1 test value, % of predicted value (mean, SD)	61.6 (13.7)	58.3 (14.1)	64.5 (12.1)	66.2 (13.6)	55.7 (15.3)	62.0 (12.9)	61.0 (13.7)	63.0 (11.2)	62.0 (15.3)

Table A2. Asthma severity: uncontrolled, high-dose ICS (+ ≥1 controller) patients age 18+.

Asthma severity	Global (n = 648)	BRA (n = 104)	MEX (n = 75)	COL (n = 79)	RUS (n = 92)	UAE (n = 48)	KSA (n = 46)	TUR (n = 131)	CHN (n = 73)
OCS use (%)*
Yes-chronic	14	8	16	15	13	10	20	21	7
Yes-acute	15	13	29	10	11	17	9	8	27
No	71	79	55	75	76	73	73	72	66
GINA step (physician-reported) (%)**
Step 1	1	–	–	–	–	2	–	–	4
Step 2	4	6	–	4	1	6	4	2	14
Step 3	24	21	28	27	26	38	15	19	25
Step 4	56	60	57	52	66	44	46	55	53
Step 5	16	13	15	18	7	10	35	24	4
Patients with Biologic add-on to current treatment (%)	6	9	29	32	13	15	9	15	29

Table A3. Exacerbation: uncontrolled, high-dose ICS (+ ≥1 controller) patients age 18+.

Exacerbation history	Global (n = 648)	BRA (n = 104)	MEX (n = 75)	COL (n = 79)	RUS (n = 92)	UAE (n = 48)	KSA (n = 46)	TUR (n = 131)	CHN (n = 73)
# of exacerbations, past 12 months (%)
0	3	1	1	8	3	6	7	2	–
1+	97	99	99	92	97	94	93	98	100
2+	80	87	79	62	90	88	80	64	99
3+	57	55	48	47	71	68	61	44	81
4+	38	35	29	35	40	44	39	31	58
# of exacerbations, past 12 months (patients with at least one exacerbation) (mean, SD)	3.9 (4.5)	4.8 (7.6)	3.3 (3.6)	3.3 (3.6)	4.1 (4.3)	3.8 (3.3)	3.3 (2.1)	3.0 (2.7)	6.0 (5.0)
# of exacerbations requiring hospitalization (patients with at least one exacerbation), past 12 months (%)
0	15	42	34	30	12	31	37	14	5
1+	76	58	66	70	88	69	63	86	995
2+	40	30	31	35	56	29	26	33	74
3+	20	13	14	17	29	16	9	14	49
4+	11	9	8	9	9	4	5	8	36
# of exacerbations requiring hospitalization, past 12 months (patients with at least one exacerbation) (mean, SD)	1.7 (2.2)	1.4 (2.7)	1.3 (1.7)	1.4 (1.6)	2.0 (1.6)	1.3 (1.7)	1.1 (1.3)	1.5 (1.3)	3.8 (3.5)
# of ER visits in the previous year* (%)
0	16	11	15	20	11	17	30	3	1
1+	84	89	85	80	89	83	70	97	99
2+	62	73	51	56	68	73	52	63	86
3+	45	51	31	49	53	56	39	46	75
4+	30	34	21	37	37	35	28	28	53
# of ER visits in the previous year* (mean, SD)	3.2 (4.2)	3.7 (5.5)	2.5 (3.5)	2.9 (2.9)	5.3 (5.6)	3.5 (4.1)	2.6 (2.9)	3.2 (3.6)	5.9 (7.5)