Identification of cytokine release syndrome and indicators of severity in retrospective databases among patients receiving immunotherapy
Abstract Cytokine release syndrome (CRS) can occur following cancer immunotherapies, but is most often mild and of limited duration. International Classification of Diseases (ICD)‐10 codes allowing identification of CRS were introduced in 2020 but may be underutilized. We evaluated the performance o...
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Wiley
2024-12-01
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| Series: | Pharmacology Research & Perspectives |
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| Online Access: | https://doi.org/10.1002/prp2.70024 |
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| author | Scott F. Huntington Dee Lin Marie‐Hélène Lafeuille Philippe Thompson‐Leduc Aditi Shah Nina Kim Laura Hester Anabelle Tardif‐Samson Bronwyn Moore Jessica Fowler Alexander Marshall Xinke Zhang Dina Gifkins Bingcao Wu |
| author_facet | Scott F. Huntington Dee Lin Marie‐Hélène Lafeuille Philippe Thompson‐Leduc Aditi Shah Nina Kim Laura Hester Anabelle Tardif‐Samson Bronwyn Moore Jessica Fowler Alexander Marshall Xinke Zhang Dina Gifkins Bingcao Wu |
| author_sort | Scott F. Huntington |
| collection | DOAJ |
| description | Abstract Cytokine release syndrome (CRS) can occur following cancer immunotherapies, but is most often mild and of limited duration. International Classification of Diseases (ICD)‐10 codes allowing identification of CRS were introduced in 2020 but may be underutilized. We evaluated the performance of a published claims‐based algorithm to detect CRS (any grade) and high‐grade CRS (HG, grades 2‐5), as well as identified indicators of HG CRS in retrospective data. Adults with low‐grade and HG CRS during an encounter coinciding with administrations of blinatumomab or chimeric antigen receptor‐T therapy were identified in three types of retrospective databases (hospital chargemaster data, electronic health records, and administrative claims). The algorithm's sensitivity in detecting any CRS and HG CRS was reported. A least absolute shrinkage and selection operator (LASSO) regression model was developed to identify indicators of HG CRS. Performance of the model was evaluated using area under the curve (AUC). The sensitivity of the algorithm to detect any grade CRS ranged between 77%–100% and between 8%–80% for HG CRS, depending on the type of database. The LASSO model identified hypotension, positive pressure (including mechanical ventilation), tocilizumab, and vasopressors as indicators of HG CRS. AUC varied between 60% and 75%. The algorithm accurately detected any grade CRS for over three‐quarters of instances, but was not as reliable for HG CRS. Results varied based on database attributes. Hypotension, vasopressors, positive pressure, and tocilizumab were associated with HG CRS and may be methodologically helpful signals of CRS severity in retrospective data. |
| format | Article |
| id | doaj-art-acc11e2a66f74b309c3835c72d12c34c |
| institution | Kabale University |
| issn | 2052-1707 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | Pharmacology Research & Perspectives |
| spelling | doaj-art-acc11e2a66f74b309c3835c72d12c34c2024-12-13T03:28:40ZengWileyPharmacology Research & Perspectives2052-17072024-12-01126n/an/a10.1002/prp2.70024Identification of cytokine release syndrome and indicators of severity in retrospective databases among patients receiving immunotherapyScott F. Huntington0Dee Lin1Marie‐Hélène Lafeuille2Philippe Thompson‐Leduc3Aditi Shah4Nina Kim5Laura Hester6Anabelle Tardif‐Samson7Bronwyn Moore8Jessica Fowler9Alexander Marshall10Xinke Zhang11Dina Gifkins12Bingcao Wu13Yale School of Medicine New Haven Connecticut USAJanssen Scientific Affairs, LLC, a Johnson and Johnson Company Horsham Pennsylvania USAAnalysis Group, Inc. Montreal Quebec CanadaAnalysis Group, Inc. Montreal Quebec CanadaAnalysis Group, Inc. Montreal Quebec CanadaJanssen Scientific Affairs, LLC, a Johnson and Johnson Company Horsham Pennsylvania USAJanssen Scientific Affairs, LLC, a Johnson and Johnson Company Horsham Pennsylvania USAAnalysis Group, Inc. Montreal Quebec CanadaAnalysis Group, Inc. Montreal Quebec CanadaJanssen Scientific Affairs, LLC, a Johnson and Johnson Company Horsham Pennsylvania USAJanssen Global Services, LLC, a Johnson and Johnson Company Raritan Pennsylvania USAJanssen Scientific Affairs, LLC, a Johnson and Johnson Company Horsham Pennsylvania USAJanssen Research and Development, LLC, a Johnson and Johnson Company Raritan Pennsylvania USAJanssen Scientific Affairs, LLC, a Johnson and Johnson Company Horsham Pennsylvania USAAbstract Cytokine release syndrome (CRS) can occur following cancer immunotherapies, but is most often mild and of limited duration. International Classification of Diseases (ICD)‐10 codes allowing identification of CRS were introduced in 2020 but may be underutilized. We evaluated the performance of a published claims‐based algorithm to detect CRS (any grade) and high‐grade CRS (HG, grades 2‐5), as well as identified indicators of HG CRS in retrospective data. Adults with low‐grade and HG CRS during an encounter coinciding with administrations of blinatumomab or chimeric antigen receptor‐T therapy were identified in three types of retrospective databases (hospital chargemaster data, electronic health records, and administrative claims). The algorithm's sensitivity in detecting any CRS and HG CRS was reported. A least absolute shrinkage and selection operator (LASSO) regression model was developed to identify indicators of HG CRS. Performance of the model was evaluated using area under the curve (AUC). The sensitivity of the algorithm to detect any grade CRS ranged between 77%–100% and between 8%–80% for HG CRS, depending on the type of database. The LASSO model identified hypotension, positive pressure (including mechanical ventilation), tocilizumab, and vasopressors as indicators of HG CRS. AUC varied between 60% and 75%. The algorithm accurately detected any grade CRS for over three‐quarters of instances, but was not as reliable for HG CRS. Results varied based on database attributes. Hypotension, vasopressors, positive pressure, and tocilizumab were associated with HG CRS and may be methodologically helpful signals of CRS severity in retrospective data.https://doi.org/10.1002/prp2.70024administrative claimsbispecific antibodieschimeric antigen receptorscytokine release syndromedrug‐related side effects and adverse reactionselectronic health records |
| spellingShingle | Scott F. Huntington Dee Lin Marie‐Hélène Lafeuille Philippe Thompson‐Leduc Aditi Shah Nina Kim Laura Hester Anabelle Tardif‐Samson Bronwyn Moore Jessica Fowler Alexander Marshall Xinke Zhang Dina Gifkins Bingcao Wu Identification of cytokine release syndrome and indicators of severity in retrospective databases among patients receiving immunotherapy Pharmacology Research & Perspectives administrative claims bispecific antibodies chimeric antigen receptors cytokine release syndrome drug‐related side effects and adverse reactions electronic health records |
| title | Identification of cytokine release syndrome and indicators of severity in retrospective databases among patients receiving immunotherapy |
| title_full | Identification of cytokine release syndrome and indicators of severity in retrospective databases among patients receiving immunotherapy |
| title_fullStr | Identification of cytokine release syndrome and indicators of severity in retrospective databases among patients receiving immunotherapy |
| title_full_unstemmed | Identification of cytokine release syndrome and indicators of severity in retrospective databases among patients receiving immunotherapy |
| title_short | Identification of cytokine release syndrome and indicators of severity in retrospective databases among patients receiving immunotherapy |
| title_sort | identification of cytokine release syndrome and indicators of severity in retrospective databases among patients receiving immunotherapy |
| topic | administrative claims bispecific antibodies chimeric antigen receptors cytokine release syndrome drug‐related side effects and adverse reactions electronic health records |
| url | https://doi.org/10.1002/prp2.70024 |
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