Using Machine Learning to Determine a Suitable Patient Population for Anakinra for the Treatment of COVID-19 Under the Emergency Use Authorization
Published 2024. This article is a U.S. Government work and is in the public domain in the USA. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics..
A randomized, double-blind, placebo-controlled study (SAVEMORE trial) provided data to support an Emergency Use Authorization (EUA) of anakinra in hospitalized adults with positive results of direct severe acute respiratory syndrome-coronavirus 2 viral testing with pneumonia requiring supplemental oxygen (low- or high-flow oxygen) who are at risk of progressing to severe respiratory failure and likely to have an elevated plasma soluble urokinase plasminogen activator receptor (suPAR). Currently, the suPAR assay is not commercially available in the United States. An alternative method was needed to identify patients that best reflect the population in the clinical trial selected based on suPAR level ≥ 6 ng/mL at baseline. A machine learning approach based on data from the SAVEMORE trial was used to develop a scoring rule to identify patients who are likely to have a suPAR level ≥ 6 ng/mL at baseline. External validation of the scoring rule was conducted with data from a different trial (SAVE). This clinical scoring rule with high positive predictive value, high specificity, reasonable sensitivity, and biological relevance is expected to identify patients who are likely to have an elevated suPAR level ≥ 6 ng/mL at baseline. As such, it is included in the EUA to identify patients that fall within the authorized population for whom the known and potential benefits outweigh the known and potential risks of anakinra.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:115 |
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| Enthalten in: |
Clinical pharmacology and therapeutics - 115(2024), 4 vom: 01. Apr., Seite 890-895 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Liu, Qi [VerfasserIn] |
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| Links: |
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| Themen: |
Biomarkers |
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| Anmerkungen: |
Date Completed 21.03.2024 Date Revised 11.04.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1002/cpt.3191 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM368386651 |
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| 520 | |a A randomized, double-blind, placebo-controlled study (SAVEMORE trial) provided data to support an Emergency Use Authorization (EUA) of anakinra in hospitalized adults with positive results of direct severe acute respiratory syndrome-coronavirus 2 viral testing with pneumonia requiring supplemental oxygen (low- or high-flow oxygen) who are at risk of progressing to severe respiratory failure and likely to have an elevated plasma soluble urokinase plasminogen activator receptor (suPAR). Currently, the suPAR assay is not commercially available in the United States. An alternative method was needed to identify patients that best reflect the population in the clinical trial selected based on suPAR level ≥ 6 ng/mL at baseline. A machine learning approach based on data from the SAVEMORE trial was used to develop a scoring rule to identify patients who are likely to have a suPAR level ≥ 6 ng/mL at baseline. External validation of the scoring rule was conducted with data from a different trial (SAVE). This clinical scoring rule with high positive predictive value, high specificity, reasonable sensitivity, and biological relevance is expected to identify patients who are likely to have an elevated suPAR level ≥ 6 ng/mL at baseline. As such, it is included in the EUA to identify patients that fall within the authorized population for whom the known and potential benefits outweigh the known and potential risks of anakinra | ||
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| 700 | 1 | |a Nikolov, Nikolay P |e verfasserin |4 aut | |
| 700 | 1 | |a Zineh, Issam |e verfasserin |4 aut | |
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