Association between pre-biologic T2-biomarker combinations and response to biologics in patients with severe asthma Article Swipe
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· 2024
· Open Access
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· DOI: https://doi.org/10.3389/fimmu.2024.1361891
Background To date, studies investigating the association between pre-biologic biomarker levels and post-biologic outcomes have been limited to single biomarkers and assessment of biologic efficacy from structured clinical trials. Aim To elucidate the associations of pre-biologic individual biomarker levels or their combinations with pre-to-post biologic changes in asthma outcomes in real-life. Methods This was a registry-based, cohort study using data from 23 countries, which shared data with the International Severe Asthma Registry (May 2017-February 2023). The investigated biomarkers (highest pre-biologic levels) were immunoglobulin E (IgE), blood eosinophil count (BEC) and fractional exhaled nitric oxide (FeNO). Pre- to approximately 12-month post-biologic change for each of three asthma outcome domains (i.e. exacerbation rate, symptom control and lung function), and the association of this change with pre-biologic biomarkers was investigated for individual and combined biomarkers. Results Overall, 3751 patients initiated biologics and were included in the analysis. No association was found between pre-biologic BEC and pre-to-post biologic change in exacerbation rate for any biologic class. However, higher pre-biologic BEC and FeNO were both associated with greater post-biologic improvement in FEV 1 for both anti-IgE and anti-IL5/5R, with a trend for anti-IL4Rα. Mean FEV 1 improved by 27-178 mL post-anti-IgE as pre-biologic BEC increased (250 to 1000 cells/µL), and by 43-216 mL and 129-250 mL post-anti-IL5/5R and -anti-IL4Rα, respectively along the same BEC gradient. Corresponding improvements along a FeNO gradient (25-100 ppb) were 41-274 mL, 69-207 mL and 148-224 mL for anti-IgE, anti-IL5/5R, and anti-IL4Rα, respectively. Higher baseline BEC was also associated with lower probability of uncontrolled asthma (OR 0.392; p=0.001) post-biologic for anti-IL5/5R. Pre-biologic IgE was a poor predictor of subsequent pre-to-post-biologic change for all outcomes assessed for all biologics. The combination of BEC + FeNO marginally improved the prediction of post-biologic FEV 1 increase (adjusted R 2 : 0.751), compared to BEC (adjusted R 2 : 0.747) or FeNO alone (adjusted R 2 : 0.743) (p=0.005 and <0.001, respectively); however, this prediction was not improved by the addition of IgE. Conclusions The ability of higher baseline BEC, FeNO and their combination to predict biologic-associated lung function improvement may encourage earlier intervention in patients with impaired lung function or at risk of accelerated lung function decline.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fimmu.2024.1361891
- https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2024.1361891/pdf
- OA Status
- gold
- Cited By
- 19
- References
- 57
- Related Works
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- OpenAlex ID
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- OpenAlex ID
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https://openalex.org/W4394961389Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3389/fimmu.2024.1361891Digital Object Identifier
- Title
-
Association between pre-biologic T2-biomarker combinations and response to biologics in patients with severe asthmaWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2024Year of publication
- Publication date
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2024-04-19Full publication date if available
- Authors
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Celeste Porsbjerg, John Townend, Céline Bergeron, George Christoff, Gregory Katsoulotos, Désirée Larenas‐Linnemann, Trung N. Tran, Riyad Al‐Lehebi, Sinthia Bosnic‐Anticevich, John Busby, Mark Hew, Κonstantinos Κostikas, Nikolaos G. Papadopoulos, Paul Pfeffer, Todor A. Popov, Chin Kook Rhee, Mohsen Sadatsafavi, Ming‐Ju Tsai, Charlotte Suppli Ulrik, Mona Al‐Ahmad, Alan Altraja, Aaron Beastall, Lakmini Bulathsinhala, Victoria Carter, Borja G. Cosío, Kirsty Fletton, Susanne Hansen, Liam G. Heaney, Richard Hubbard, Piotr Kuna, Ruth Murray, Tatsuya Nagano, Laura Pini, Diana Jimena Cano Rosales, Florence Schleich, Michael E. Wechsler, Rita Amaral, Arnaud Bourdin, Guy Brusselle, Wenjia Chen, Li Ping Chung, Eve Denton, João Fonseca, Flavia Hoyte, David J. Jackson, Rohit Katial, Bruce Kirenga, Mariko Siyue Koh, Agnieszka Ławkiedraj, Lauri Lehtimäki, Mei Fong Liew, Bassam Mahboub, Neil Martin, Andrew Menzies‐Gow, Pee Hwee Pang, Andriana Ι. Papaioannou, Pujan H. Patel, Luis Pérez de Llano, Matthew Peters, L Ricciardi, Bellanid Rodríguez-Cáceres, Iván Solarte, Tunn Ren Tay, Carlos A. Torres‐Duque, Eileen Wang, Martina Zappa, John Abisheganaden, Karin Dahl Assing, Richard W. Costello, Peter G. Gibson, Enrico Heffler, Jorge Máspero, Stefania Nicola, Diahn‐Warng Perng, Francesca Puggioni, Sundeep Salvi, Chau‐Chyun Sheu, Concetta Sirena, Camille Taillé, Tze Lee Tan, Leif Bjermer, Giorgio Walter Canonica, Takashi Iwanaga, Libardo Jiménez-Maldonado, Christian Taube, Luisa Brussino, David PriceList of authors in order
- Landing page
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https://doi.org/10.3389/fimmu.2024.1361891Publisher landing page
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https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2024.1361891/pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2024.1361891/pdfDirect OA link when available
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Medicine, Asthma, Association (psychology), Inflammatory response, Immunology, Psychology, Inflammation, PsychotherapistTop concepts (fields/topics) attached by OpenAlex
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19Total citation count in OpenAlex
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2025: 18, 2024: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.elucidate | 31 |
| abstract_inverted_index.encourage | 346 |
| abstract_inverted_index.gradient. | 219 |
| abstract_inverted_index.increased | 199 |
| abstract_inverted_index.initiated | 136 |
| abstract_inverted_index.predictor | 265 |
| abstract_inverted_index.Background | 0 |
| abstract_inverted_index.assessment | 21 |
| abstract_inverted_index.associated | 170, 247 |
| abstract_inverted_index.biologics. | 276 |
| abstract_inverted_index.biomarkers | 19, 77, 124 |
| abstract_inverted_index.countries, | 62 |
| abstract_inverted_index.eosinophil | 86 |
| abstract_inverted_index.fractional | 90 |
| abstract_inverted_index.function), | 115 |
| abstract_inverted_index.individual | 36, 128 |
| abstract_inverted_index.marginally | 283 |
| abstract_inverted_index.prediction | 286, 319 |
| abstract_inverted_index.real-life. | 50 |
| abstract_inverted_index.structured | 26 |
| abstract_inverted_index.subsequent | 267 |
| abstract_inverted_index.Conclusions | 328 |
| abstract_inverted_index.accelerated | 359 |
| abstract_inverted_index.association | 6, 118, 145 |
| abstract_inverted_index.biomarkers. | 131 |
| abstract_inverted_index.cells/µL), | 203 |
| abstract_inverted_index.combination | 278, 338 |
| abstract_inverted_index.improvement | 174, 344 |
| abstract_inverted_index.pre-to-post | 43, 152 |
| abstract_inverted_index.probability | 250 |
| abstract_inverted_index.Pre-biologic | 260 |
| abstract_inverted_index.anti-IL4Rα, | 240 |
| abstract_inverted_index.anti-IL4Rα. | 187 |
| abstract_inverted_index.anti-IL5/5R, | 182, 238 |
| abstract_inverted_index.anti-IL5/5R. | 259 |
| abstract_inverted_index.associations | 33 |
| abstract_inverted_index.combinations | 41 |
| abstract_inverted_index.exacerbation | 109, 156 |
| abstract_inverted_index.improvements | 221 |
| abstract_inverted_index.intervention | 348 |
| abstract_inverted_index.investigated | 76, 126 |
| abstract_inverted_index.pre-biologic | 8, 35, 79, 123, 149, 164, 197 |
| abstract_inverted_index.respectively | 214 |
| abstract_inverted_index.uncontrolled | 252 |
| abstract_inverted_index.-anti-IL4Rα, | 213 |
| abstract_inverted_index.2017-February | 73 |
| abstract_inverted_index.Corresponding | 220 |
| abstract_inverted_index.International | 68 |
| abstract_inverted_index.approximately | 97 |
| abstract_inverted_index.investigating | 4 |
| abstract_inverted_index.post-anti-IgE | 195 |
| abstract_inverted_index.post-biologic | 12, 99, 173, 257, 288 |
| abstract_inverted_index.respectively. | 241 |
| abstract_inverted_index.&lt;0.001, | 315 |
| abstract_inverted_index.immunoglobulin | 82 |
| abstract_inverted_index.respectively); | 316 |
| abstract_inverted_index.registry-based, | 55 |
| abstract_inverted_index.post-anti-IL5/5R | 211 |
| abstract_inverted_index.biologic-associated | 341 |
| abstract_inverted_index.pre-to-post-biologic | 268 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 90 |
| countries_distinct_count | 29 |
| institutions_distinct_count | 87 |
| citation_normalized_percentile.value | 0.98235219 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |