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Abstract

Objective:

To explore whether baseline clinical biomarkers and characteristics can be used to predict the responsiveness of omalizumab.

Methods:

We retrospectively analyzed a cohort of patients with severe asthma who received omalizumab treatment and collected their baseline data and relevant laboratory examination results along with case records of omalizumab treatment responsiveness after 16 weeks. We compared the differences in variables between the group of patients that responded to omalizumab therapy and the non-responder group, and then performed univariate and multivariate logistic regression. Finally, we analyzed the difference in response rate for subgroups by selecting cut-off values for the variables using Fisher’s exact probability method.

Results:

This retrospective, single-center observational study enrolled 32 patients with severe asthma who were prescribed daily high-dose inhaled corticosteroids and long-acting β2 receptor agonists on long-acting muscarinic receptor antagonists with or without OCS. Data on age, sex, BMI, bronchial thermoplasty, FeNO, serum total IgE, FEV1, blood eosinophils, induced sputum eosinophils, blood basophils, and complications were not significantly different between the responder and non-responder groups. In the univariate and multivariate logistic regression, all the variants were not significant, and we were unable to build a regression model. We used normal high values and the mean or median of variables as cut-off values to create patient subgroups for the variables and found no significant difference in the omalizumab response rate between the subgroups.

Conclusion:

The responsiveness of omalizumab is not associated with pretreatment clinical biomarkers, and these biomarkers should not be used to predict the responsiveness of omalizumab.

Keywords

baseline clinical characteristics biomarker omalizumab response severe asthma

Introduction

Omalizumab, the first available antibody for the biological treatment of severe asthma, was approved in China in 2018.¹ And China’s Food and Drug Administration approved omalizumab for the treatment of moderate to severe persistent allergic asthma in adults and adolescents (6 years and older) who still cannot control symptoms after treatment with inhaled glucocorticoids combined with β2 agonists. However, omalizumab is not affective for all cases of severe asthma.^2–4 Omalizumab is generally well tolerated; however, it may be associated with adverse reactions, such as anaphylactic or anaphylactoid reactions^5–9 (reporting rate of 0.09% of patients), pyrexia, and urticaria.¹⁰ Moreover, omalizumab is not cost-effective,¹¹ and it may need to be used for a long time. Some patients may also experience a relapse of symptoms after withdrawal of the drug.¹² Therefore, individualized precision treatment using biomarkers must be developed.

Studies have found that Galectin-3,^13,14 serum periostin,¹⁵ baseline serum chemokine interferon-γ inducible protein 10 kDa (CXCL10), interleukin (IL)-12,¹⁶ and IL-13 in induced sputum supernatants¹⁷ may be biomarkers for predicting the response to omalizumab treatment. Serum-free immunoglobulin E (IgE) levels¹⁸ and changes in total serum IgE¹⁹ during follow-up can also be used as biomarkers for omalizumab treatment; however, it is not easy to detect free IgE clinically. The literature reported that fractional exhaled nitric oxide (FeNO), blood eosinophil count, and forced expiratory volume in 1 s (FEV1) are clinical indicators for responsiveness to omalizumab.^20–23 Nevertheless, both prospective real-world²⁴ and retrospective studies^25,26 have found that biomarker levels before omalizumab treatment do not affect the response.

To evaluate the clinical indicators of omalizumab responsiveness, we retrospectively analyzed the omalizumab cohort data of patients with severe asthma in the China-Japan Friendship Hospital since 2018.

Methods

Study design and participants

This single-center, non-interventional, retrospective, observational study was performed at the China-Japan Friendship Hospital from 1 January 2018 to 31 December 2020 using data from the medical records of patients with severe allergic asthma treated with omalizumab. This real-life study was approved by the Ethics Committee of the China-Japan Friendship Hospital at 17 August 2017 (No. 2017-89), and informed consent was obtained from all patients with adequate notification.

Inclusion criteria were any patient ⩾12 years of age; patients included in the study were treated with omalizumab for poorly controlled severe asthma; a daily high-dose inhaled corticosteroid and long-acting β2 receptor agonists along with long-acting muscarinic receptor antagonists were prescribed; and a physician evaluated the patient’s response to omalizumab after 16 weeks of treatment. Patients who declined the use of their medical data for research purposes were excluded according to the ethics committee requirements.

Data collection process

Investigators created an Excel spreadsheet for patient information, including the name, sex, baseline age, stature, weight, FeNO, eosinophil count, basophil count, total serum IgE, FEV1, predicted value for FEV1%, induced sputum eosinophil count, comorbidities, the intake of oral steroid hormones, and omalizumab response after 16 weeks of treatment.

Outcomes

The outcome was a response to omalizumab treatment after 16 weeks according to the Global Evaluation of Treatment Effectiveness (GETE) scale. Responder GETE was classified as excellent (complete control of asthma) or good (marked improvement), while non-responder GETE was classified as moderate (discernible, but a limited improvement), poor (no appreciable change), or worsening (worsening).

Statistical analysis

Statistical analysis was performed using the R4.0.2 software. Descriptive analyses of quantitative variables are expressed as mean and standard deviation for normally distributed variables or as median and interquartile range for the variables not normally distributed. Qualitative variables were presented as the number of patients for each category and percentage. Logistic regression and subgroup analyses were used to analyze the biomarkers of omalizumab responsiveness. All statistical tests were two-sided, and the α risk was set at 0.05.

Results

Subjects

Of the 136 patients with severe asthma, 41 patients had ⩾1 administration of omalizumab, and five patients discontinued treatment after the first administration for various reasons, including anaphylactic reactions (n = 1), economic pressures (n = 3), and loss of follow-up (n = 1). In the 36 patients with severe asthma who continued the treatment after the first administration and were evaluated after 16 weeks, 32 patients had complete baseline data and were analyzed (Figure 1).

Figure 1.

Study flowchart.

Patient characteristics are presented in Table 1.

Table 1.

Demographics and clinical characteristics at baseline (time of omalizumab initiation) in severe patients.

	Overall	Responder	Non-responder	p value
Subjects	32	23	9
Sex				1
Male	9 (28.1)	7 (30.4)	2 (22.2)
Female	23 (71.9)	16 (69.6)	7 (77.8)
Age (year)	54.66 ± 12.14	55.22 ± 13.30	53.22 ± 8.98	0.683
BMI (kg/m²)	25.10 ± 3.20	25.28 ± 3.42	24.64 ± 2.68	0.615
Comorbidity
Anaphylactic rhinitis	22 (68.8)	14 (60.9)	8 (88.9)	0.210
Nasal polyp	3 (9.4)	2 (8.7)	1 (11.1)	1
Nasosinusitis	24 (75.0)	18 (78.3)	6 (66.7)	0.654
Reflux esophagitis	9 (28.1)	8 (34.8)	1 (11.1)	0.383
Dermatitis	2 (6.2)	2 (8.7)	0 (0.0)	1
Bronchial Thermoplasty	9 (28.1)	8 (34.8)	1 (11.1)	0.383
OCS	20 (62.5)	14 (60.9)	6 (66.7)	1
Daily dose of OCS (mg)	12.50 [0, 20]	10.00 [0, 20]	15.00 [0, 20]	0.729
Baseline biomarker
FeNO (ppb)	41.50[25.75, 85.00]	43.00[26.00, 72.50]	40.00[26.00, 110.00]	0.753
Sputum eosinophil %	33.95 ± 23.87	33.40 ± 21.68	35.33 ± 30.20	0.841
Serum total IgE (IU/ml)	312.50[155.75, 706.00]	307[123.00, 728.00]	318[210.00, 504.00]	0.586
Eosinophil (cells/μl)	458.75 ± 343.27	506.09 ± 343.15	337.78 ± 331.50	0.218
Eosinophil %	5.40 [2.55, 10.68]	5.90 [4.05, 12.00]	2.60 [0.60, 7.60]	0.137
Basophil (cells/μl)	43.12 ± 21.77	37.78 ± 21.67	45.22 ± 21.92	0.393
Basophil %	0.63 ± 0.33	0.51 ± 0.25	0.68 ± 0.36	0.209
FEV1 (l)	1.74 ± 0.65	1.81 ± 0.65	1.58 ± 0.66	0.393
FEV1% predicted	69.55 ± 24.11	70.95 ± 24.12	65.97 ± 25.14	0.607

Data presented as n, mean ± SD or n (%) unless otherwise stated.

Ba, blood basophilic count; BMI, body mass index; Eos, blood eosinophil count; FeNO, fractional exhaled nitric oxide; FEV1, forced expiratory volume in 1 s; OCS, oral corticosteroid.

Omalizumab was prescribed as an add-on therapy according to body weight and total serum IgE level based on the drug instructions. This was to help improve asthma control in patients with severe asthma who had poor asthma control even with ongoing prescriptions of daily high-dose inhaled corticosteroids along with a long-acting β2-agonist and a long-acting muscarinic receptor antagonist with or without oral corticosteroids (OCS). After 16 weeks of treatment with omalizumab, 23 of the 32 patients in the cohort were classified as responders on the GETE scale, and 9 patients were classified as non-responders. The response rate for omalizumab was 71.87%. Twenty patients were prescribed OCS, and 9 patients had previously undergone bronchial thermoplasty.

We used the ‘pastecs’ package to test the normality of the continuous variables and found that FeNO, the percentage of eosinophils, total serum IgE and the OCS dose did not conform to the normal distribution; other factors such as age, body mass index (BMI), eosinophil count, basophil count, the percentage of basophils, FEV1, predicted FEV1%, and the proportion of induced sputum eosinophils accorded with the normal distribution. Consequently, we compared the baseline data between responder and non-responder groups using the ‘epiDisplay’ package in the R 4.0.2 software, which showed that all the variables were not statistically significant (p >0.05).

Logistic regression

Univariate logistic regression analysis was used to analyze the effects of all the variables on the patient response to omalizumab, and found that none of the factors were statistically significant (Table 2). Before performing multivariate logistic regression, we used the ‘car’ package to explore the multicollinearity of the continuous variables. Multicollinearity analysis showed that the square root of the predicted variance expansion factors for eosinophils, eosinophil%, basophils, basophil%, FEV1, and FEV1% were greater than 2, and all these variants were multicollinear. The multivariate logistic regression results also showed that none of the variables were statistically significant (p = 1).

Table 2.

Univariate logistic regression of omalizumab response.

	Univariate logistic regression
	OR (95% CI)	p value
Age	1.0139 [0.9493–1.0846]	0.6720
Sex	1.5313 [0.2778–12.0424]	0.6436
BMI	1.0670 [0.8327–1.3760]	0.6029
FeNO	0.9930 [0.9790–1.0055]	0.2700
Sputum eosinophil %	0.9965 [0.9637–1.0305]	0.8347
Serum total IgE	0.9997 [0.9981–1.0015]	0.7438
Eosinophil	1.0017 [0.9992–1.0046]	0.2166
Eosinophil %	1.1370 [0.9650–1.3964]	0.1588
Basophil	1.0168 [0.9804–1.0586]	0.3822
Basophil %	6.2404 [0.4766–172.4217]	0.2111
FEV1	1.7152 [0.5134–6.0933]	0.3813
FEV1% predicted	1.0091 [0.9766–1.0460]	0.5950
Bronchial thermoplasty	4.2667 [0.6136–86.4961]	0.2061
OCS	0.7778 [0.1364–3.7943]	0.7610
Daily dose of OCS	0.9874 [0.9201–1.059]	0.7172
Anaphylactic rhinitis	0.1944 [0.0096–1.3332]	0.1521
Nasal polyp	0.7619 [0.0638–17.7315]	0.8335
Nasosinusitis	1.8 [0.2985–9.9039]	0.4989
Reflux esophagitis	4.2667 [0.6136–86.4961]	0.2061
Dermatitis	18,233,491[8.484198e–184-NA]	0.9952

BMI, body mass index; CI, confidence interval; FEV1, forced expiratory volume in 1 s; OCS, oral corticosteroid; OR, odds ratio.

Subgroup analysis

Patients were divided into two groups according to the mean age of 55 years. The response rate of patients older than or equal to 55 years was 77.78%; it was 64.29% in patients younger than 55 years. The p value of the two groups was 0.4533 by Fisher’s exact probability method, which was not statistically significant.

The response rate of men with severe asthma was 77.78%, and that of women was 69.57%. The p value was 1, which was not statistically significant.

Obesity generally influences the prognosis of bronchial asthma, especially severe asthma. A BMI greater than 24 kg/m² was considered overweight. In this study, patients with a BMI greater than 24 kg/m² had a response rate of 76.19%, and those with a BMI less than 24 kg/m² had a response rate of 63.64%. The p value of the two groups was 0.6808, which was not statistically significant.

Bronchial thermoplasty is an endoscopic treatment for uncontrolled asthma that was approved for clinical use in late 2013 in China which is performed earlier than omalizumab.²⁷ In this study, nine patients underwent bronchial thermoplasty, and the response rate of these patients who also received omalizumab was 88.89%, while the response rate of patients who did not undergo bronchial thermoplasty receiving omalizumab was 65.22%. Statistical analysis was conducted between the two groups, with a p value equal to 0.383, which was not statistically significant.

The results showed that these comorbidities, including allergic rhinitis, nasosinusitis, nasal polyps, dermatitis, and gastroesophageal reflux, had no effect on omalizumab response, the p values were 0.21, 0.6545, 1, 1, and 0.3830, respectively. The omalizumab response rate was independent of the oral glucocorticoid and its dose also.

Omalizumab response in different cut-off values of variants

The difference in the omalizumab response between different cut-off values for the baseline biomarkers was also evaluated. Among 32 patients, 27 had FeNO levels ⩾20 ppb and 5 had FeNO levels <20 ppb. Moreover, the response rate to treatment with omalizumab was similar irrespective of the level of FeNO, with a cut-off of either 20 ppb (p = 0.6042), which was recommended by the guidelines, or the median value of 41.5 ppb (p = 1; Figure 2).

Figure 2.

Omalizumab response in subgroup and different cut-off values of variants.

Among the 32 patients, the median total serum IgE level was 312.5 IU/ml. For 16 patients, this level was higher than 312.5 IU/ml, and the responder rate was 68.75%, while for 24 patients, the serum IgE level was higher than the standard upper limit of 161 IU/ml, with the rate of response being 66.67%. Regardless of the cut-off value, there was no difference in the omalizumab response rate based on the Fisher exact probability test; the p values were 0.3858 and 1.0000, respectively (Figure 2).

In terms of eosinophils, we separately evaluated peripheral blood eosinophils and eosinophils in the induced sputum. The American Thoracic Society (ATS)/European Respiratory Society (ERS) guidelines,²⁸ along with the Global Initiative for Asthma (GINA)²⁹ guidelines, recommend a response cut-off value of 260 cells/μl for omalizumab, with omalizumab response rates of 78.95% and 61.54% above 260 cells/μl and below 260 cells/μl, respectively. No significant difference in response rate was found between these two groups using a cut-off value of 260 cells/μl. In this cohort, the mean blood eosinophil count was approximately 450 cells/μl, and the omalizumab response rate was similar to that when 450 cells/μl was used as a cut-off value (Figure 2).

The expected value of eosinophils in the induced sputum is generally less than 2%, the omalizumab response rate of more than 2% was 71.435%, and less than 2% was 75%, which was not statistically significant, and the p value was 1. The average value for induced sputum in this cohort was approximately 34%, which was used as the cut-off value, and the response rates were 73.33% and 70.59%, respectively. Regardless of the cut-off value, the response rate was not statistically significant.

The cohort was divided into three groups based on the percentage of FEV1 in the predicted values of 50% and 80%. The omalizumab response rates were 77.8%, 72.22%, and 60%, respectively. There were no statistically significant differences between the response rates of the three groups. The response was similar, using either 80% or 70%, or even 50% as a cut-off value. The same was true for basophils.

Discussion

This report suggests that, in China, the response to omalizumab treatment in a patient with severe asthma does not vary with pretreatment biomarkers such as FeNO, serum total IgE, blood eosinophil count, induced sputum eosinophil count, predicted FEV1% and blood basophil count. Baseline clinical characteristics such as age, sex, BMI, bronchial thermoplasty, oral glucocorticoids, or complications such as allergic rhinitis, sinusitis, nasal polyps, gastroesophageal reflux, and dermatitis are also not associated with the response to omalizumab.

Hanania et al.²³ found that the level of FeNO provided information on subgroups that may significantly benefit from omalizumab therapy using data from patients with severe allergic asthma in the EXTRA study. Bhutani et al.²⁰ demonstrated that FeNO may be a useful biomarker to identify patients who may benefit from omalizumab in a 1-year observational study in Canada. Brooks et al.³⁰ showed that using FeNO to predict the effectiveness of omalizumab can reduce patients’ expected costs. Moreover, the ERS/ATS guidelines²⁸ conditionally recommended using an FeNO cut-off of ⩾19.5 ppb to identify cases of severe allergic asthma that were more likely to benefit from anti-IgE treatment. However, in our retrospective study, the response rate in patients with an FeNO level of ⩾20 ppb was 74.07%, while that for patients with an FeNO level of <20 ppb was 60%; no significant difference in response rate was found between these two subgroups. Similar results were obtained for a cut-off value of 41.5 ppb. We found that FeNO was not a useful biomarker to predict the effectiveness of omalizumab. Our results were similar to the results of a retrospective study²⁵ that enrolled 56 allergic asthma patients, and the results of the PROSPERO real-world study,²⁴ which was a prospective study that enrolled 806 patients with allergic asthma.

Bronchial asthma can manifest as an increase in peripheral blood eosinophil count and eosinophil infiltration in the airways, especially in cases of severe asthma. Nevertheless, this study found that regardless of the level of peripheral blood eosinophils or induced sputum eosinophils, there was no significant difference in the response to omalizumab, and eosinophil count could not be used as a biomarker for omalizumab treatment. This is the first study to explore whether induced sputum eosinophils can guide the administration of omalizumab, regardless of whether the subgroups were divided by 2% or 34%.

The PROSPERO study by Casale et al.,²⁴ the retrospective study by Kavati et al.,²⁵ and the STELLAIR study by Humbert et al.²⁶ showed that peripheral blood eosinophils cannot be used as a biomarker for omalizumab responsiveness. However, in the EXTRA study,²³ the response to omalizumab therapy was better in the high peripheral blood eosinophil subgroup than in the low eosinophil subgroup, indicating that patients with a high eosinophil count may benefit from omalizumab therapy. A high eosinophil count may be a potential biomarker for the assessment of omalizumab treatment effects. The ERS/ATS²⁸ and GINA guidelines²⁹ recommend using a blood eosinophil cut-off value of ⩾260 cells/μl to select patients with severe asthma to be treated with omalizumab; however, further discussion and research are warranted for this cut-off value. In our research, for the subgroup with an eosinophil count of ⩾260 cells/μl, the response rate was 78.95%, while the response rate was 61.54%; for the subgroup with an eosinophil count of ⩾ 450 cells/μl, the response rate was 78.57%, while the response rate was 66.67% in the low subgroup. With either cut-off value, the response rates were similar.

Tajiri et al.¹⁸ found that serum-free IgE levels during the follow-up for omalizumab treatment may have predicted the response to omalizumab in their prospective observational study. In addition, Li et al.¹⁹ showed that the changes in total serum IgE levels may help evaluate responses to omalizumab treatment. Naumova et al.³¹ provided evidence that measuring cumulative levels of IgE specific for respiratory allergens serve as biomarker to enhance the success of IgE-targeted therapy. However, in our study, we did not find the baseline IgE level to predict the response to omalizumab; similar to the preliminary bioinformatics analysis results from a study by ourselves.³²

Kallieri et al.¹⁷ showed that a lower baseline FEV1 was a predictor of response to omalizumab. Unfortunately, our retrospective analysis did not show similar results, which is consistent with the results of the study by Asano et al.³³ We also did not find that baseline blood basophils could be a useful biomarker, contrary to the results of the study by Poddighe and Vangelista³⁴ that suggested that basophils may affect the clinical success of omalizumab.

The subgroup analysis by Asaon et al.³³ showed that sex and age did not affect the omalizumab response. This is consistent with the results of the present study, where the response rate of males was 77.78%, and that of females was 69.57%, and the comparison between the two groups was not statistically significant. The response rate was 77.78% in elderly patients and 64.29% in younger patients, with no significant difference between the two groups. These results are also consistent with the results of our previous bioinformatics analysis GSE134544.³²

Gu et al.³⁵ demonstrated that BMI significantly affected the outcome of omalizumab treatment. However, in our retrospective analysis, we could not conclude that BMI influenced the efficacy of omalizumab treatment. We used the cut-off value of 24 kg/m² for a high BMI, while the cut-off value in the study by Gu et al. was 30 kg/m². We set the cut-off value at 30 kg/m² and analyzed the retrospective cohort study again with no meaningful results.

Among 32 patients with severe asthma, 9 patients had undergone bronchial thermoplasty. This study was the first to analyze the effect of bronchial thermoplasty on the efficacy of omalizumab. The results showed there was no significant difference in response rate between the patients who had undergone bronchial thermoplasty and those who had not. Thermoplasty did not affect the efficacy of omalizumab.

In terms of comorbidities, we evaluated allergic rhinitis, sinusitis, nasal polyps, dermatitis, and gastroesophageal reflux. Subgroup analysis showed no effect of these comorbidities on the outcome of omalizumab treatment, with P values of 0.2100, 0.6545, 1, 1, and 0.3830, respectively. In the study by Asano et al.,³³ the subgroup analysis showed that the p value of allergic rhinitis was 0.0516, and the p value of atopic dermatitis was 0.6682, both of which were not statistically significant, which is consistent with the results of our study. Asano et al. did not investigate the effects of sinusitis, nasal polyps, and gastroesophageal reflux on the outcomes of omalizumab treatment. Other comorbidities in their study, such as liver injury, kidney injury, and eosinophilia, did not significantly affect the efficacy of omalizumab treatment. The intake of OCS and OCS dose had no effect on omalizumab efficacy.

While the results of some studies are similar to ours, many other studies have results that are inconsistent with those of our study. Thus, further research is warranted on the prediction of the effectiveness of omalizumab using clinical biomarkers. Our study also had some limitations: first, although we included patients in our hospital who received omalizumab treatment in the past 3 years, the sample size was small, which may be because of there was little time to market omalizumab in our country. Furthermore, doctors are still exploring patient selection criteria for this drug. Second, this was a retrospective study, and a few patients were excluded due to a lack of baseline data. Third, this was a single-center study. All patients received omalizumab treatment in our hospital, but a small number of patients came from elsewhere in the country.

Therefore, a large-scale, national, multi-center prospective study must be conducted to evaluate biomarkers that can predict the responsiveness of omalizumab. This will help clinicians prescribe omalizumab to patients who would benefit from it. In addition to pretreatment clinical biomarkers, studies have also reported that some molecules, such as CXCL10, IL12, Galectin-3, CD3E andC4Ma3, can be used as markers to predict omalizumab responsiveness.^{13,14,16,32,36} Baseline molecular biomarkers may be the future of clinical biomarkers that predict the effectiveness of omalizumab.

Footnotes

Acknowledgements

None.

Declarations

ORCID iDs

Qing Zhang

Jiangtao Lin

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Role of clinical biomarkers in predicting the effectiveness of omalizumab