Latent Class Trajectory Modeling of 2‐Component Disease Activity Score in 28 Joints Identifies Multiple Rheumatoid Arthritis Phenotypes of Response to Biologic Disease‐Modifying Antirheumatic Drugs
Objective To determine whether using a reweighted disease activity score that better reflects joint synovitis, i.e., the 2‐component Disease Activity Score in 28 joints (DAS28) (based on swollen joint count and C‐reactive protein level), produces more clinically relevant treatment outcome trajectori...
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creator | Dagliati, Arianna Plant, Darren Nair, Nisha Jani, Meghna Amico, Beatrice Peek, Niels Morgan, Ann W. Isaacs, John Wilson, Anthony G. Hyrich, Kimme L. Geifman, Nophar Barton, Anne |
description | Objective
To determine whether using a reweighted disease activity score that better reflects joint synovitis, i.e., the 2‐component Disease Activity Score in 28 joints (DAS28) (based on swollen joint count and C‐reactive protein level), produces more clinically relevant treatment outcome trajectories compared to the standard 4‐component DAS28.
Methods
Latent class mixed modeling of response to biologic treatment was applied to 2,991 rheumatoid arthritis (RA) patients in whom treatment with a biologic disease‐modifying antirheumatic drug was being initiated within the Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate cohort, using both 4‐component and 2‐component DAS28 scores as outcome measures. Patient groups with similar trajectories were compared in terms of pretreatment baseline characteristics (including disability and comorbidities) and follow‐up characteristics (including antidrug antibody events, adherence to treatments, and blood drug levels). We compared the trajectories obtained using the 4‐ and 2‐component scores to determine which characteristics were better captured by each.
Results
Using the 4‐component DAS28, we identified 3 trajectory groups, which is consistent with previous findings. We showed that the 4‐component DAS28 captures information relating to depression. Using the 2‐component DAS28, 7 trajectory groups were identified; among them, distinct groups of nonresponders had a higher incidence of respiratory comorbidities and a higher proportion of antidrug antibody events. We also identified a group of patients for whom the 2‐component DAS28 scores remained relatively low; this group included a high percentage of patients who were nonadherent to treatment. This highlights the utility of both the 4‐ and 2‐component DAS28 for monitoring different components of disease activity.
Conclusion
Here we show that the 2‐component modified DAS28 defines important biologic and clinical phenotypes associated with treatment outcome in RA and characterizes important underlying response mechanisms to biologic drugs. |
doi_str_mv | 10.1002/art.41379 |
format | Article |
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To determine whether using a reweighted disease activity score that better reflects joint synovitis, i.e., the 2‐component Disease Activity Score in 28 joints (DAS28) (based on swollen joint count and C‐reactive protein level), produces more clinically relevant treatment outcome trajectories compared to the standard 4‐component DAS28.
Methods
Latent class mixed modeling of response to biologic treatment was applied to 2,991 rheumatoid arthritis (RA) patients in whom treatment with a biologic disease‐modifying antirheumatic drug was being initiated within the Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate cohort, using both 4‐component and 2‐component DAS28 scores as outcome measures. Patient groups with similar trajectories were compared in terms of pretreatment baseline characteristics (including disability and comorbidities) and follow‐up characteristics (including antidrug antibody events, adherence to treatments, and blood drug levels). We compared the trajectories obtained using the 4‐ and 2‐component scores to determine which characteristics were better captured by each.
Results
Using the 4‐component DAS28, we identified 3 trajectory groups, which is consistent with previous findings. We showed that the 4‐component DAS28 captures information relating to depression. Using the 2‐component DAS28, 7 trajectory groups were identified; among them, distinct groups of nonresponders had a higher incidence of respiratory comorbidities and a higher proportion of antidrug antibody events. We also identified a group of patients for whom the 2‐component DAS28 scores remained relatively low; this group included a high percentage of patients who were nonadherent to treatment. This highlights the utility of both the 4‐ and 2‐component DAS28 for monitoring different components of disease activity.
Conclusion
Here we show that the 2‐component modified DAS28 defines important biologic and clinical phenotypes associated with treatment outcome in RA and characterizes important underlying response mechanisms to biologic drugs.</description><identifier>ISSN: 2326-5191</identifier><identifier>EISSN: 2326-5205</identifier><identifier>DOI: 10.1002/art.41379</identifier><identifier>PMID: 32475078</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Aged ; Antibodies ; Antirheumatic Agents - therapeutic use ; Arthritis ; Arthritis, Rheumatoid - diagnosis ; Arthritis, Rheumatoid - drug therapy ; Disability Evaluation ; Drugs ; Female ; Genetics ; Health services ; Humans ; Joint diseases ; Joints (anatomy) ; Latent class analysis ; Male ; Medical treatment ; Middle Aged ; Modelling ; Patients ; Phenotype ; Phenotypes ; Rheumatoid arthritis ; Severity of Illness Index ; Synovitis ; Treatment Outcome</subject><ispartof>Arthritis & rheumatology (Hoboken, N.J.), 2020-10, Vol.72 (10), p.1632-1642</ispartof><rights>2020 The Authors. published by Wiley Periodicals LLC on behalf of American College of Rheumatology.</rights><rights>2020 The Authors. Arthritis & Rheumatology published by Wiley Periodicals LLC on behalf of American College of Rheumatology.</rights><rights>2020. This article is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3889-cae64dc14a06f693f8f28e7192f3b94594a04a604024e4eb547e058fe23795c83</citedby><cites>FETCH-LOGICAL-c3889-cae64dc14a06f693f8f28e7192f3b94594a04a604024e4eb547e058fe23795c83</cites><orcidid>0000-0003-4855-3926 ; 0000-0002-5041-0409 ; 0000-0002-1487-277X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fart.41379$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fart.41379$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,1417,27923,27924,45573,45574</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32475078$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Dagliati, Arianna</creatorcontrib><creatorcontrib>Plant, Darren</creatorcontrib><creatorcontrib>Nair, Nisha</creatorcontrib><creatorcontrib>Jani, Meghna</creatorcontrib><creatorcontrib>Amico, Beatrice</creatorcontrib><creatorcontrib>Peek, Niels</creatorcontrib><creatorcontrib>Morgan, Ann W.</creatorcontrib><creatorcontrib>Isaacs, John</creatorcontrib><creatorcontrib>Wilson, Anthony G.</creatorcontrib><creatorcontrib>Hyrich, Kimme L.</creatorcontrib><creatorcontrib>Geifman, Nophar</creatorcontrib><creatorcontrib>Barton, Anne</creatorcontrib><creatorcontrib>BRAGGSS Study Group</creatorcontrib><creatorcontrib>for the BRAGGSS Study Group</creatorcontrib><title>Latent Class Trajectory Modeling of 2‐Component Disease Activity Score in 28 Joints Identifies Multiple Rheumatoid Arthritis Phenotypes of Response to Biologic Disease‐Modifying Antirheumatic Drugs</title><title>Arthritis & rheumatology (Hoboken, N.J.)</title><addtitle>Arthritis Rheumatol</addtitle><description>Objective
To determine whether using a reweighted disease activity score that better reflects joint synovitis, i.e., the 2‐component Disease Activity Score in 28 joints (DAS28) (based on swollen joint count and C‐reactive protein level), produces more clinically relevant treatment outcome trajectories compared to the standard 4‐component DAS28.
Methods
Latent class mixed modeling of response to biologic treatment was applied to 2,991 rheumatoid arthritis (RA) patients in whom treatment with a biologic disease‐modifying antirheumatic drug was being initiated within the Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate cohort, using both 4‐component and 2‐component DAS28 scores as outcome measures. Patient groups with similar trajectories were compared in terms of pretreatment baseline characteristics (including disability and comorbidities) and follow‐up characteristics (including antidrug antibody events, adherence to treatments, and blood drug levels). We compared the trajectories obtained using the 4‐ and 2‐component scores to determine which characteristics were better captured by each.
Results
Using the 4‐component DAS28, we identified 3 trajectory groups, which is consistent with previous findings. We showed that the 4‐component DAS28 captures information relating to depression. Using the 2‐component DAS28, 7 trajectory groups were identified; among them, distinct groups of nonresponders had a higher incidence of respiratory comorbidities and a higher proportion of antidrug antibody events. We also identified a group of patients for whom the 2‐component DAS28 scores remained relatively low; this group included a high percentage of patients who were nonadherent to treatment. This highlights the utility of both the 4‐ and 2‐component DAS28 for monitoring different components of disease activity.
Conclusion
Here we show that the 2‐component modified DAS28 defines important biologic and clinical phenotypes associated with treatment outcome in RA and characterizes important underlying response mechanisms to biologic drugs.</description><subject>Aged</subject><subject>Antibodies</subject><subject>Antirheumatic Agents - therapeutic use</subject><subject>Arthritis</subject><subject>Arthritis, Rheumatoid - diagnosis</subject><subject>Arthritis, Rheumatoid - drug therapy</subject><subject>Disability Evaluation</subject><subject>Drugs</subject><subject>Female</subject><subject>Genetics</subject><subject>Health services</subject><subject>Humans</subject><subject>Joint diseases</subject><subject>Joints (anatomy)</subject><subject>Latent class analysis</subject><subject>Male</subject><subject>Medical treatment</subject><subject>Middle Aged</subject><subject>Modelling</subject><subject>Patients</subject><subject>Phenotype</subject><subject>Phenotypes</subject><subject>Rheumatoid arthritis</subject><subject>Severity of Illness Index</subject><subject>Synovitis</subject><subject>Treatment Outcome</subject><issn>2326-5191</issn><issn>2326-5205</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>EIF</sourceid><recordid>eNp1kc1OGzEURq0KVBCw6AtUlrpiEbA9nh8vp6FQUFCrNF2PHM914mgyntqeotnxCLwWr9EnwWFId3hjSz4639X9EPpEyQUlhF1KFy44TXLxAR2zhGWTlJH0YP-mgh6hM-83JB6Rk4ykH9FRwniekrw4Rs8zGaANeNpI7_HCyQ2oYN2A720NjWlX2GrM_j0-Te22s-0OvTIepAdcqmD-mjDgX8o6wKbFrMB31rTB49s6kkYb8Pi-b4LpGsDzNfRbGaypcenC2plgPP65htaGoYtgDJqDjyHRHSz-amxjV0bt8-IMcSajh91QZbS70bcjXL_yp-hQy8bD2dt9gn5ff1tMv09mP25up-VsopKiEBMlIeO1olySTGci0YVmBeRUMJ0sBU9F_OAyI5wwDhyWKc-BpIUGFlecqiI5QV9Gb-fsnx58qDa2d22MrBjnGWM0EzxS5yOlnPXega46Z7bSDRUl1a63KvZWvfYW2c9vxn65hfo_uW8pApcj8GAaGN43VeV8MSpfAP3NpsY</recordid><startdate>202010</startdate><enddate>202010</enddate><creator>Dagliati, Arianna</creator><creator>Plant, Darren</creator><creator>Nair, Nisha</creator><creator>Jani, Meghna</creator><creator>Amico, Beatrice</creator><creator>Peek, Niels</creator><creator>Morgan, Ann W.</creator><creator>Isaacs, John</creator><creator>Wilson, Anthony G.</creator><creator>Hyrich, Kimme L.</creator><creator>Geifman, Nophar</creator><creator>Barton, Anne</creator><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>WIN</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QL</scope><scope>7QP</scope><scope>7T5</scope><scope>7TM</scope><scope>7U7</scope><scope>C1K</scope><scope>H94</scope><scope>K9.</scope><orcidid>https://orcid.org/0000-0003-4855-3926</orcidid><orcidid>https://orcid.org/0000-0002-5041-0409</orcidid><orcidid>https://orcid.org/0000-0002-1487-277X</orcidid></search><sort><creationdate>202010</creationdate><title>Latent Class Trajectory Modeling of 2‐Component Disease Activity Score in 28 Joints Identifies Multiple Rheumatoid Arthritis Phenotypes of Response to Biologic Disease‐Modifying Antirheumatic Drugs</title><author>Dagliati, Arianna ; Plant, Darren ; Nair, Nisha ; Jani, Meghna ; Amico, Beatrice ; Peek, Niels ; Morgan, Ann W. ; Isaacs, John ; Wilson, Anthony G. ; Hyrich, Kimme L. ; Geifman, Nophar ; Barton, Anne</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3889-cae64dc14a06f693f8f28e7192f3b94594a04a604024e4eb547e058fe23795c83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Aged</topic><topic>Antibodies</topic><topic>Antirheumatic Agents - therapeutic use</topic><topic>Arthritis</topic><topic>Arthritis, Rheumatoid - diagnosis</topic><topic>Arthritis, Rheumatoid - drug therapy</topic><topic>Disability Evaluation</topic><topic>Drugs</topic><topic>Female</topic><topic>Genetics</topic><topic>Health services</topic><topic>Humans</topic><topic>Joint diseases</topic><topic>Joints (anatomy)</topic><topic>Latent class analysis</topic><topic>Male</topic><topic>Medical treatment</topic><topic>Middle Aged</topic><topic>Modelling</topic><topic>Patients</topic><topic>Phenotype</topic><topic>Phenotypes</topic><topic>Rheumatoid arthritis</topic><topic>Severity of Illness Index</topic><topic>Synovitis</topic><topic>Treatment Outcome</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dagliati, Arianna</creatorcontrib><creatorcontrib>Plant, Darren</creatorcontrib><creatorcontrib>Nair, Nisha</creatorcontrib><creatorcontrib>Jani, Meghna</creatorcontrib><creatorcontrib>Amico, Beatrice</creatorcontrib><creatorcontrib>Peek, Niels</creatorcontrib><creatorcontrib>Morgan, Ann W.</creatorcontrib><creatorcontrib>Isaacs, John</creatorcontrib><creatorcontrib>Wilson, Anthony G.</creatorcontrib><creatorcontrib>Hyrich, Kimme L.</creatorcontrib><creatorcontrib>Geifman, Nophar</creatorcontrib><creatorcontrib>Barton, Anne</creatorcontrib><creatorcontrib>BRAGGSS Study Group</creatorcontrib><creatorcontrib>for the BRAGGSS Study Group</creatorcontrib><collection>Wiley-Blackwell Open Access Titles</collection><collection>Wiley Free Content</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Immunology Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><jtitle>Arthritis & rheumatology (Hoboken, N.J.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dagliati, Arianna</au><au>Plant, Darren</au><au>Nair, Nisha</au><au>Jani, Meghna</au><au>Amico, Beatrice</au><au>Peek, Niels</au><au>Morgan, Ann W.</au><au>Isaacs, John</au><au>Wilson, Anthony G.</au><au>Hyrich, Kimme L.</au><au>Geifman, Nophar</au><au>Barton, Anne</au><aucorp>BRAGGSS Study Group</aucorp><aucorp>for the BRAGGSS Study Group</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Latent Class Trajectory Modeling of 2‐Component Disease Activity Score in 28 Joints Identifies Multiple Rheumatoid Arthritis Phenotypes of Response to Biologic Disease‐Modifying Antirheumatic Drugs</atitle><jtitle>Arthritis & rheumatology (Hoboken, N.J.)</jtitle><addtitle>Arthritis Rheumatol</addtitle><date>2020-10</date><risdate>2020</risdate><volume>72</volume><issue>10</issue><spage>1632</spage><epage>1642</epage><pages>1632-1642</pages><issn>2326-5191</issn><eissn>2326-5205</eissn><abstract>Objective
To determine whether using a reweighted disease activity score that better reflects joint synovitis, i.e., the 2‐component Disease Activity Score in 28 joints (DAS28) (based on swollen joint count and C‐reactive protein level), produces more clinically relevant treatment outcome trajectories compared to the standard 4‐component DAS28.
Methods
Latent class mixed modeling of response to biologic treatment was applied to 2,991 rheumatoid arthritis (RA) patients in whom treatment with a biologic disease‐modifying antirheumatic drug was being initiated within the Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate cohort, using both 4‐component and 2‐component DAS28 scores as outcome measures. Patient groups with similar trajectories were compared in terms of pretreatment baseline characteristics (including disability and comorbidities) and follow‐up characteristics (including antidrug antibody events, adherence to treatments, and blood drug levels). We compared the trajectories obtained using the 4‐ and 2‐component scores to determine which characteristics were better captured by each.
Results
Using the 4‐component DAS28, we identified 3 trajectory groups, which is consistent with previous findings. We showed that the 4‐component DAS28 captures information relating to depression. Using the 2‐component DAS28, 7 trajectory groups were identified; among them, distinct groups of nonresponders had a higher incidence of respiratory comorbidities and a higher proportion of antidrug antibody events. We also identified a group of patients for whom the 2‐component DAS28 scores remained relatively low; this group included a high percentage of patients who were nonadherent to treatment. This highlights the utility of both the 4‐ and 2‐component DAS28 for monitoring different components of disease activity.
Conclusion
Here we show that the 2‐component modified DAS28 defines important biologic and clinical phenotypes associated with treatment outcome in RA and characterizes important underlying response mechanisms to biologic drugs.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>32475078</pmid><doi>10.1002/art.41379</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0003-4855-3926</orcidid><orcidid>https://orcid.org/0000-0002-5041-0409</orcidid><orcidid>https://orcid.org/0000-0002-1487-277X</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Aged Antibodies Antirheumatic Agents - therapeutic use Arthritis Arthritis, Rheumatoid - diagnosis Arthritis, Rheumatoid - drug therapy Disability Evaluation Drugs Female Genetics Health services Humans Joint diseases Joints (anatomy) Latent class analysis Male Medical treatment Middle Aged Modelling Patients Phenotype Phenotypes Rheumatoid arthritis Severity of Illness Index Synovitis Treatment Outcome |
title | Latent Class Trajectory Modeling of 2‐Component Disease Activity Score in 28 Joints Identifies Multiple Rheumatoid Arthritis Phenotypes of Response to Biologic Disease‐Modifying Antirheumatic Drugs |
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