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Can we predict who ...
Can we predict who will benefit most from biologics in severe asthma? : A post-hoc analysis of two phase 3 trials
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- Chen, Wenjia (författare)
- Natl Univ Singapore, Saw Swee Hock Sch Publ Hlth, MD1-Tahir Fdn Bldg, 12 Sci Dr 2, Singapore 117549, Singapore.
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- Reddel, Helen K. (författare)
- Univ Sydney, Woolcock Inst Med Res, Sydney, Australia.
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- FitzGerald, J. Mark (författare)
- Univ British Columbia, Fac Pharmaceut Sci, Resp Evaluat Sci Program, Vancouver, BC, Canada.
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- Beasley, Richard (författare)
- Med Res Inst New Zealand, Wellington, New Zealand.
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- Janson, Christer (författare)
- Uppsala universitet,Arbets- och miljömedicin,Lung- allergi- och sömnforskning,Klinisk fysiologi,Uppsala Univ, Dept Med Sci, Uppsala, Sweden.
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- Sadatsafavi, Mohsen (författare)
- Univ British Columbia, Fac Pharmaceut Sci, Resp Evaluat Sci Program, Vancouver, BC, Canada.
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Natl Univ Singapore, Saw Swee Hock Sch Publ Hlth, MD1-Tahir Fdn Bldg, 12 Sci Dr 2, Singapore 117549, Singapore Univ Sydney, Woolcock Inst Med Res, Sydney, Australia. (creator_code:org_t)
- BioMed Central (BMC), 2023
- 2023
- Engelska.
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Ingår i: Respiratory Research. - : BioMed Central (BMC). - 1465-9921 .- 1465-993X. ; 24:1
- Relaterad länk:
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https://doi.org/10.1...
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https://uu.diva-port... (primary) (Raw object)
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- BackgroundIndividualized prediction of treatment response may improve the value proposition of advanced treatment options in severe asthma. This study aimed to investigate the combined capacity of patient characteristics in predicting treatment response to mepolizumab in patients with severe asthma.MethodsPatient-level data were pooled from two multinational phase 3 trials of mepolizumab in severe eosinophilic asthma. We fitted penalized regression models to quantify reductions in the rate of severe exacerbations and the 5-item Asthma Control Questionnaire (ACQ5) score. The capacity of 15 covariates towards predicting treatment response was quantified by the Gini index (measuring disparities in treatment benefit) as well as observed treatment benefit within the quintiles of predicted treatment benefit.ResultsThere was marked variability in the ability of patient characteristics to predict treatment response; covariates explained greater heterogeneity in predicting treatment response to asthma control than to exacerbation frequency (Gini index 0.35 v. 0.24). Key predictors for treatment benefit for severe exacerbations included exacerbation history, blood eosinophil count, baseline ACQ5 score and age, and those for symptom control included blood eosinophil count and presence of nasal polyps. Overall, the average reduction in exacerbations was 0.90/year (95%CI, 0.87-0.92) and average reduction in ACQ5 score was 0.18 (95% CI, 0.02-0.35). Among the top 20% of patients for predicted treatment benefit, exacerbations were reduced by 2.23/year (95% CI, 2.03-2.43) and ACQ5 score were reduced by 0.59 (95% CI, 0.19-0.98). Among the bottom 20% of patients for predicted treatment benefit, exacerbations were reduced by 0.25/year (95% CI, 0.16-0.34) and ACQ5 by -0.20 (95% CI, -0.51 to 0.11).ConclusionA precision medicine approach based on multiple patient characteristics can guide biologic therapy in severe asthma, especially in identifying patients who will not benefit as much from therapy. Patient characteristics had a greater capacity to predict treatment response to asthma control than to exacerbation.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Lungmedicin och allergi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Respiratory Medicine and Allergy (hsv//eng)
Nyckelord
- Severe asthma
- Biologics
- Mepolizumab
- Prediction
- Treatment response
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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