Evidence map›Paper›PMID 33447398›Full record

ArticleJournal of thoracic disease2020

Prediction of clinical response to omalizumab in moderate-to-severe asthma patients using the change in total serum IgE level.

Bohou Li, Minyu Huang, Shuyu Huang, Xiaoli Zeng, Yafei Yuan, Xianru Peng, Wenqu Zhao, Yanmei Ye, Changhui Yu, Laiyu Liu and 3 more

Open access · diamondAbstract read
In one paragraph

Article in Journal of thoracic disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.4field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 21 citations in OpenAlex.

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  9. Biomarkers for selecting biologic therapies in asthma.Therapeutic advances in respiratory disease
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 2 institutions in 1 country.

Bohou LiChronic Airways Diseases Laboratory, Department of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Minyu HuangChronic Airways Diseases Laboratory, Department of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Shuyu HuangChronic Airways Diseases Laboratory, Department of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Xiaoli ZengChronic Airways Diseases Laboratory, Department of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Yafei YuanChronic Airways Diseases Laboratory, Department of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Xianru PengChronic Airways Diseases Laboratory, Department of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Wenqu ZhaoChronic Airways Diseases Laboratory, Department of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Yanmei YeChronic Airways Diseases Laboratory, Department of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Changhui YuChronic Airways Diseases Laboratory, Department of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Laiyu LiuChronic Airways Diseases Laboratory, Department of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Chunquan OuDepartment of the Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China.
Shaoxi CaiChronic Airways Diseases Laboratory, Department of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Haijin ZhaoChronic Airways Diseases Laboratory, Department of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Nanfang Hospital · CNSouthern Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOmalizumab (OMA) is an effective anti-immunoglobulin E (IgE) treatment for moderate-to-severe asthma. However, predicting an individual's response is difficult. Monitoring change of total serum IgE may be useful for predicting the response to OMA. The purpose of this study was to determine if measuring the change in total IgE level could predict the response to OMA in patients with moderate-to-severe asthma.

methodsThis study included 25 patients (11 females and 14 males; mean age =46.1 years; mean pre-bronchodilator FEV1% =67.8%) with moderate-to-severe asthma. All patients were treated with OMA, and total IgE serum concentrations were measured at baseline before treatment (median baseline total serum IgE =210 IU/mL) and at 4 weeks after beginning treatment. Patients were divided into responders (i.e., excellent or good response) and non-responders (i.e., moderate or poor response) using the global treatment effectiveness (GETE) response method after 16 weeks of treatment. The characteristics of responders and non-responders were compared, and receiver operating characteristic (ROC) curve analysis was used to determine the ability of change in IgE level to predict treatment response.

resultsThere were 20 responders (80%) and 5 non-responders (20%), and responders demonstrated better improvements of asthma control test (ACT) and asthma control questionnaire (ACQ) scores, and reduction of oral corticosteroid use as compared with non-responders. Twenty-one patients had a total serum IgE 4-week-to-baseline ratio ≥2, and 20 of the patients responded to OMA. The area under the ROC curve (AUC) for baseline IgE level for predicting treatment response was 0.53 (95% CI: 0.18-0.88), and that of the week 4 IgE level was 0.69 (95% CI: 0.42-0.96). Using a cutoff value of 2, the 4-week: baseline IgE ratio achieved the highest AUC of 0.87 (95% CI: 0.64-1), with a sensitivity and specificity of 100% and 80%, respectively, for predicting treatment response.

conclusionsA total week 4 serum IgE level:baseline level ratio ≥2 can predict the response to OMA in patients with moderate-to-severe asthma after 16 weeks of treatment with high likelihood. Monitoring changes of total IgE level in asthma patients treated OMA may be useful for predicting clinical response.

Indexed as

Asthmaimmunoglobulin E (IgE)omalizumab (OMA)treatment effectiveness

Identifiers

PMID33447398
PMCPMC7797858
OpenAlexW3112742104

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.