Decision Impact Analysis to Measure the Influence of Molecular Signature Response Classifier Testing on Treatment Selection in Rheumatoid Arthritis
Abstract Introduction Clinical guidelines offer little guidance for treatment selection following inadequate response to conventional synthetic disease-modifying antirheumatic drug (csDMARD) in rheumatoid arthritis (RA). A molecular signature response classifier (MSRC) was validated to predict tumor...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Adis, Springer Healthcare
2023-11-01
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| Series: | Rheumatology and Therapy |
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| Online Access: | https://doi.org/10.1007/s40744-023-00618-1 |
| _version_ | 1797349756184297472 |
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| author | Jeffrey R. Curtis Vibeke Strand Steven J. Golombek George A. Karpouzas Lixia Zhang Angus Wong Krishna Patel Jennifer Dines Viatcheslav R. Akmaev |
| author_facet | Jeffrey R. Curtis Vibeke Strand Steven J. Golombek George A. Karpouzas Lixia Zhang Angus Wong Krishna Patel Jennifer Dines Viatcheslav R. Akmaev |
| author_sort | Jeffrey R. Curtis |
| collection | DOAJ |
| description | Abstract Introduction Clinical guidelines offer little guidance for treatment selection following inadequate response to conventional synthetic disease-modifying antirheumatic drug (csDMARD) in rheumatoid arthritis (RA). A molecular signature response classifier (MSRC) was validated to predict tumor necrosis factor inhibitor (TNFi) inadequate response. The decision impact of MSRC results on biologic and targeted synthetic disease-modifying antirheumatic drug (b/tsDMARD) selection was evaluated. Methods This is an analysis of AIMS, a longitudinal, prospective database of patients with RA tested using the MSRC. This study assessed selection of b/tsDMARDs class after MSRC testing by surveying physicians, the rate of b/tsDMARD prescriptions aligning with MSRC results, and the percentage of physicians utilizing MSRC results for decision-making. Results Of 1018 participants, 70.7% (720/1018) had treatment selected after receiving MSRC results. In this MSRC-informed cohort, 75.6% (544/720) of patients received a b/tsDMARD aligned with MSRC results, and 84.6% (609/720) of providers reported using MSRC results to guide treatment selection. The most prevalent reason reported (8.2%, 59/720) for not aligning treatment selection with MSRC results from the total cohort was health insurance coverage issues. Conclusion This study showed that rheumatologists reported using the MSRC test to guide b/tsDMARD selection for patients with RA. In most cases, MSRC test results appeared to influence clinical decision-making according to physician self-report. Wider adoption of precision medicine tools like the MSRC could support rheumatologists and patients in working together to achieve optimal outcomes for RA. |
| first_indexed | 2024-03-08T12:34:59Z |
| format | Article |
| id | doaj.art-fe1216b916824c379498e0495b271723 |
| institution | Directory Open Access Journal |
| issn | 2198-6576 2198-6584 |
| language | English |
| last_indexed | 2024-03-08T12:34:59Z |
| publishDate | 2023-11-01 |
| publisher | Adis, Springer Healthcare |
| record_format | Article |
| series | Rheumatology and Therapy |
| spelling | doaj.art-fe1216b916824c379498e0495b2717232024-01-21T12:34:57ZengAdis, Springer HealthcareRheumatology and Therapy2198-65762198-65842023-11-01111617710.1007/s40744-023-00618-1Decision Impact Analysis to Measure the Influence of Molecular Signature Response Classifier Testing on Treatment Selection in Rheumatoid ArthritisJeffrey R. Curtis0Vibeke Strand1Steven J. Golombek2George A. Karpouzas3Lixia Zhang4Angus Wong5Krishna Patel6Jennifer Dines7Viatcheslav R. Akmaev8Division of Clinical Immunology and Rheumatology, The University of Alabama at BirminghamDivision of Immunology/Rheumatology, Stanford UniversityAllergy, Asthma and Arthritis Associates, St. Clare’s HealthHarbor-UCLA Medical CenterScipher Medicine CorporationScipher Medicine CorporationScipher Medicine CorporationScipher Medicine CorporationScipher Medicine CorporationAbstract Introduction Clinical guidelines offer little guidance for treatment selection following inadequate response to conventional synthetic disease-modifying antirheumatic drug (csDMARD) in rheumatoid arthritis (RA). A molecular signature response classifier (MSRC) was validated to predict tumor necrosis factor inhibitor (TNFi) inadequate response. The decision impact of MSRC results on biologic and targeted synthetic disease-modifying antirheumatic drug (b/tsDMARD) selection was evaluated. Methods This is an analysis of AIMS, a longitudinal, prospective database of patients with RA tested using the MSRC. This study assessed selection of b/tsDMARDs class after MSRC testing by surveying physicians, the rate of b/tsDMARD prescriptions aligning with MSRC results, and the percentage of physicians utilizing MSRC results for decision-making. Results Of 1018 participants, 70.7% (720/1018) had treatment selected after receiving MSRC results. In this MSRC-informed cohort, 75.6% (544/720) of patients received a b/tsDMARD aligned with MSRC results, and 84.6% (609/720) of providers reported using MSRC results to guide treatment selection. The most prevalent reason reported (8.2%, 59/720) for not aligning treatment selection with MSRC results from the total cohort was health insurance coverage issues. Conclusion This study showed that rheumatologists reported using the MSRC test to guide b/tsDMARD selection for patients with RA. In most cases, MSRC test results appeared to influence clinical decision-making according to physician self-report. Wider adoption of precision medicine tools like the MSRC could support rheumatologists and patients in working together to achieve optimal outcomes for RA.https://doi.org/10.1007/s40744-023-00618-1Molecular signaturePrecision medicineResponse classifierRheumatoid arthritisTreatment selection |
| spellingShingle | Jeffrey R. Curtis Vibeke Strand Steven J. Golombek George A. Karpouzas Lixia Zhang Angus Wong Krishna Patel Jennifer Dines Viatcheslav R. Akmaev Decision Impact Analysis to Measure the Influence of Molecular Signature Response Classifier Testing on Treatment Selection in Rheumatoid Arthritis Rheumatology and Therapy Molecular signature Precision medicine Response classifier Rheumatoid arthritis Treatment selection |
| title | Decision Impact Analysis to Measure the Influence of Molecular Signature Response Classifier Testing on Treatment Selection in Rheumatoid Arthritis |
| title_full | Decision Impact Analysis to Measure the Influence of Molecular Signature Response Classifier Testing on Treatment Selection in Rheumatoid Arthritis |
| title_fullStr | Decision Impact Analysis to Measure the Influence of Molecular Signature Response Classifier Testing on Treatment Selection in Rheumatoid Arthritis |
| title_full_unstemmed | Decision Impact Analysis to Measure the Influence of Molecular Signature Response Classifier Testing on Treatment Selection in Rheumatoid Arthritis |
| title_short | Decision Impact Analysis to Measure the Influence of Molecular Signature Response Classifier Testing on Treatment Selection in Rheumatoid Arthritis |
| title_sort | decision impact analysis to measure the influence of molecular signature response classifier testing on treatment selection in rheumatoid arthritis |
| topic | Molecular signature Precision medicine Response classifier Rheumatoid arthritis Treatment selection |
| url | https://doi.org/10.1007/s40744-023-00618-1 |
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