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- Caronna, Edoardo, et al.
(author)
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Redefining migraine prevention: early treatment with anti-CGRP monoclonal antibodies enhances response in the real world
- 2024
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In: JOURNAL OF NEUROLOGY NEUROSURGERY AND PSYCHIATRY. - 0022-3050 .- 1468-330X.
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Journal article (peer-reviewed)abstract
- Background Anti-CGRP monoclonal antibodies (anti-CGRP MAbs) are approved and available treatments for migraine prevention. Patients do not respond alike and many countries have reimbursement policies, which hinder treatments to those who might respond. This study aimed to investigate clinical factors associated with good and excellent response to anti-CGRP MAbs at 6 months. Methods European multicentre, prospective, real-world study, including high-frequency episodic or chronic migraine (CM) patients treated since March 2018 with anti-CGRP MAbs. We defined good and excellent responses as >= 50% and >= 75% reduction in monthly headache days (MHD) at 6 months, respectively. Generalised mixed-effect regression models (GLMMs) were used to identify variables independently associated with treatment response. Results Of the 5818 included patients, 82.3% were females and the median age was 48.0 (40.0-55.0) years. At baseline, the median of MHD was 20.0 (14.0-28.0) days/months and 72.2% had a diagnosis of CM. At 6 months (n=4963), 56.5% (2804/4963) were good responders and 26.7% (1324/4963) were excellent responders. In the GLMM model, older age (1.08 (95% CI 1.02 to 1.15), p=0.016), the presence of unilateral pain (1.39 (95% CI 1.21 to 1.60), p<0.001), the absence of depression (0.840 (95% CI 0.731 to 0.966), p=0.014), less monthly migraine days (0.923 (95% CI 0.862 to 0.989), p=0.023) and lower Migraine Disability Assessment at baseline (0.874 (95% CI 0.819 to 0.932), p<0.001) were predictors of good response (AUC of 0.648 (95% CI 0.616 to 0.680)). These variables were also significant predictors of excellent response (AUC of 0.691 (95% CI 0.651 to 0.731)). Sex was not significant in the GLMM models. Conclusions This is the largest real-world study of migraine patients treated with anti-CGRP MAbs. It provides evidence that higher migraine frequency and greater disability at baseline reduce the likelihood of responding to anti-CGRP MAbs, informing physicians and policy-makers on the need for an earlier treatment in order to offer the best chance of treatment success.
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| 2. |
- Fuentes, Manuel, et al.
(author)
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Exploring High-Throughput Immunoassays for Biomarker Validation in Rheumatic Diseases in the Context of the Human Proteome Project
- 2023
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In: Journal of Proteome Research. - : American Chemical Society. - 1535-3893 .- 1535-3907. ; 22:4, s. 1105-1115
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Journal article (peer-reviewed)abstract
- Rheumatic diseases are high prevalence pathologies with different etiology and evolution and low sensitivity in clinical diagnosis. Therefore, it is necessary to develop an early diagnosis method which allows personalized treatment, depending on the specific pathology. The biology/disease initiative, at Human Proteome Project, is an integrative approach to identify relevant proteins in the human proteome associated with pathologies. A previously reported literature data mining analysis, which identified proteins related to osteoarthritis (OA), rheumatoid arthritis (RA), and psoriatic arthritis (PSA) was used to establish a systematic prioritization of potential biomarkers candidates for further evaluation by functional proteomics studies. The aim was to study the protein profile of serum samples from patients with rheumatic diseases such as OA, RA, and PSA. To achieve this goal, customized antibody microarrays (containing 151 antibodies targeting 121 specific proteins) were used to identify biomarkers related to early and specific diagnosis in a screening of 960 serum samples (nondepleted) (OA, n = 480; RA, n = 192; PSA, n = 288). This functional proteomics screening has allowed the determination of a panel (30 serum proteins) as potential biomarkers for these rheumatic diseases, displaying receiver operating characteristics curves with area under the curve values of 80-90%.
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| 3. |
- Juanes-Velasco, Pablo, et al.
(author)
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Deciphering Biomarkers for Leptomeningeal Metastasis in Malignant Hemopathies (Lymphoma/Leukemia) Patients by Comprehensive Multipronged Proteomics Characterization of Cerebrospinal Fluid
- 2022
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In: Cancers. - : MDPI AG. - 2072-6694. ; 14:2
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Journal article (peer-reviewed)abstract
- Simple Summary The early diagnosis of leptomeningeal disease is a challenge because it is asymptomatic in the early stages. Consequently, it is important to identify a panel of biomarkers to help in its diagnosis and/or prognosis. For this purpose, we explored a multipronged proteomics approach in cerebrospinal fluid (CSF) to determine a potential panel of biomarkers. Thus, a systematic and exhaustive characterization of more than 300 CSF samples was performed by an integrated approach by Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) and functional proteomics analysis to establish protein profiles, which were useful for developing a panel of biomarkers validated by in silico approaches. In the present work, leptomeningeal disease, a very destructive form of systemic cancer, was characterized from several proteomics points of view. This pathology involves the invasion of the leptomeninges by malignant tumor cells. The tumor spreads to the central nervous system through the cerebrospinal fluid (CSF) and has a very grim prognosis; the average life expectancy of patients who suffer it does not exceed 3 months. The early diagnosis of leptomeningeal disease is a challenge because, in most of the cases, it is an asymptomatic pathology. When the symptoms are clear, the disease is already in the very advanced stages and life expectancy is low. Consequently, there is a pressing need to determine useful CSF proteins to help in the diagnosis and/or prognosis of this disease. For this purpose, a systematic and exhaustive proteomics characterization of CSF by multipronged proteomics approaches was performed to determine different protein profiles as potential biomarkers. Proteins such as PTPRC, SERPINC1, sCD44, sCD14, ANPEP, SPP1, FCGR1A, C9, sCD19, and sCD34, among others, and their functional analysis, reveals that most of them are linked to the pathology and are not detected on normal CSF. Finally, a panel of biomarkers was verified by a prediction model for leptomeningeal disease, showing new insights into the research for potential biomarkers that are easy to translate into the clinic for the diagnosis of this devastating disease.
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