SAT0385 Disease Activity Patterns Over Time in Patients with SLE – a Retrospective Descriptive Analysis of the Hopkins Lupus Cohort
BackgroundSystemic Lupus Erythematosus (SLE) is a multi-systemic inflammatory disease, characterized by an extreme variability of its expression, both between individuals and within individuals, over time. Overall disease activity appears to be an important predictor of both mortality and organ dama...
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description | BackgroundSystemic Lupus Erythematosus (SLE) is a multi-systemic inflammatory disease, characterized by an extreme variability of its expression, both between individuals and within individuals, over time. Overall disease activity appears to be an important predictor of both mortality and organ damage. It is therefore important to understand the burden of disease course over time among patients with SLE (Barr et al. 1999)ObjectivesTo discern and describe SLE disease activity patterns over time by analyzing data from the Hopkins Lupus Cohort.MethodsDisease activity was retrospectively studied in a cohort of 2386 consecutive SLE patients followed up quarterly for 1-28 years (10 367 person-years of followup). SLE disease activity patterns were defined using 1) Physician Global Assessment (PGA) and 2) SLE Disease Activity Index (SLEDAI), including serology: Long Quiescent (LQ), SLEDAI/PGA=0 for 1 year at all visits; Relapsing-Remitting (RR), periods of disease activity (SLEDAI/PGA>0) interspersed with periods of disease inactivity (SLEDAI/PGA=0) at 1 or more visits during 1 year; Chronic Active (CA), SLEDAI/PGA scores are >0 for 1 year at all visits. Disease activity at yearly intervals (“1-year blocks”) was readily classified into 1 of the 3 major patterns for each patient. The pattern in each patient of 3 consecutive followup years (“3-year blocks”) was also determined: Persistent Long Quiescent (pLQ), LQ pattern in each of the 3 years; Persistent Remissing-Remitting (pRR), RR pattern in each of the 3 years; Persistent Chronic Active (pCA), CA pattern in each of the 3 years; Mixed, at least 2 different pattern types during 3 consecutive years. The frequency of different pattern groups (LQ, RR, CA) in each “1-year-block” and pattern subgroups (pLQ, pRR, pCA, Mixed) in each “3-year-block” of followup was examined.ResultsThree major patterns of SLE disease activity were identified: LQ, RR, and CA. The RR pattern accounted for the greatest proportion of followup time for both the SLEDAI and PGA, representing 48.3% and 51.8% of total person-years, respectively. The CA pattern was the second most frequent pattern observed (SLEDAI 35.5%, PGA 38.5% of total person-years). The least prevalent pattern was the LQ (SLEDAI 16.1%, PGA 9.5% of total person-years), indicating that 655 patients experienced 1674 LQ “1-year-blocks”, and 352 patients experienced 981 LQ “1-year-blocks”, using SLEDAI and PGA, respectively. When disease activity was defined within 3-year intervals |
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Overall disease activity appears to be an important predictor of both mortality and organ damage. It is therefore important to understand the burden of disease course over time among patients with SLE (Barr et al. 1999)ObjectivesTo discern and describe SLE disease activity patterns over time by analyzing data from the Hopkins Lupus Cohort.MethodsDisease activity was retrospectively studied in a cohort of 2386 consecutive SLE patients followed up quarterly for 1-28 years (10 367 person-years of followup). SLE disease activity patterns were defined using 1) Physician Global Assessment (PGA) and 2) SLE Disease Activity Index (SLEDAI), including serology: Long Quiescent (LQ), SLEDAI/PGA=0 for 1 year at all visits; Relapsing-Remitting (RR), periods of disease activity (SLEDAI/PGA>0) interspersed with periods of disease inactivity (SLEDAI/PGA=0) at 1 or more visits during 1 year; Chronic Active (CA), SLEDAI/PGA scores are >0 for 1 year at all visits. Disease activity at yearly intervals (“1-year blocks”) was readily classified into 1 of the 3 major patterns for each patient. The pattern in each patient of 3 consecutive followup years (“3-year blocks”) was also determined: Persistent Long Quiescent (pLQ), LQ pattern in each of the 3 years; Persistent Remissing-Remitting (pRR), RR pattern in each of the 3 years; Persistent Chronic Active (pCA), CA pattern in each of the 3 years; Mixed, at least 2 different pattern types during 3 consecutive years. The frequency of different pattern groups (LQ, RR, CA) in each “1-year-block” and pattern subgroups (pLQ, pRR, pCA, Mixed) in each “3-year-block” of followup was examined.ResultsThree major patterns of SLE disease activity were identified: LQ, RR, and CA. The RR pattern accounted for the greatest proportion of followup time for both the SLEDAI and PGA, representing 48.3% and 51.8% of total person-years, respectively. The CA pattern was the second most frequent pattern observed (SLEDAI 35.5%, PGA 38.5% of total person-years). The least prevalent pattern was the LQ (SLEDAI 16.1%, PGA 9.5% of total person-years), indicating that 655 patients experienced 1674 LQ “1-year-blocks”, and 352 patients experienced 981 LQ “1-year-blocks”, using SLEDAI and PGA, respectively. When disease activity was defined within 3-year intervals, the Mixed pattern was the most common for both the SLEDAI and LAI, representing 55% of total “3-year blocks”. The pRR and pCA patterns were intermediate and similar in frequency (pRR 19.8%, pCA 20.7%). The pLQ was the least frequent pattern (SLEDAI: 5.7% and PGA: 2.8%). The most common discrepancy between instruments was that the PGA demonstrated CA when the SLEDAI showed an RR pattern. The SLEDAI was more likely to depict the LQ pattern than was the PGA (Table 1.)ConclusionsIn this large cohort, the three major patterns of SLE disease activity as originally identified by Barr et al. were confirmed. In the present study, the RR pattern appeared to be the most prevalent pattern type. Long quiescence was achieved in a subset of patients. Over a 3-year perspective almost half the patient maintained their disease activity pattern.Disclosure of InterestNone declared</description><identifier>ISSN: 0003-4967</identifier><identifier>EISSN: 1468-2060</identifier><identifier>DOI: 10.1136/annrheumdis-2015-eular.4660</identifier><identifier>CODEN: ARDIAO</identifier><language>eng</language><publisher>London: BMJ Publishing Group LTD</publisher><ispartof>Annals of the rheumatic diseases, 2015-06, Vol.74 (Suppl 2), p.798-799</ispartof><rights>2015, Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions</rights><rights>Copyright: 2015 (c) 2015, Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-b1859-ab8887527eee4670f4a748036165271afe014a3cbf2cda49839b308e6306a1153</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttp://ard.bmj.com/content/74/Suppl_2/798.3.full.pdf$$EPDF$$P50$$Gbmj$$H</linktopdf><linktohtml>$$Uhttp://ard.bmj.com/content/74/Suppl_2/798.3.full$$EHTML$$P50$$Gbmj$$H</linktohtml><link.rule.ids>114,115,315,782,786,3200,23580,27933,27934,77610,77641</link.rule.ids></links><search><creatorcontrib>Györi, N.</creatorcontrib><creatorcontrib>Chatzidionysiou, A.</creatorcontrib><creatorcontrib>Magder, L.</creatorcontrib><creatorcontrib>van Vollenhoven, R.</creatorcontrib><creatorcontrib>Petri, M.</creatorcontrib><title>SAT0385 Disease Activity Patterns Over Time in Patients with SLE – a Retrospective Descriptive Analysis of the Hopkins Lupus Cohort</title><title>Annals of the rheumatic diseases</title><description>BackgroundSystemic Lupus Erythematosus (SLE) is a multi-systemic inflammatory disease, characterized by an extreme variability of its expression, both between individuals and within individuals, over time. Overall disease activity appears to be an important predictor of both mortality and organ damage. It is therefore important to understand the burden of disease course over time among patients with SLE (Barr et al. 1999)ObjectivesTo discern and describe SLE disease activity patterns over time by analyzing data from the Hopkins Lupus Cohort.MethodsDisease activity was retrospectively studied in a cohort of 2386 consecutive SLE patients followed up quarterly for 1-28 years (10 367 person-years of followup). SLE disease activity patterns were defined using 1) Physician Global Assessment (PGA) and 2) SLE Disease Activity Index (SLEDAI), including serology: Long Quiescent (LQ), SLEDAI/PGA=0 for 1 year at all visits; Relapsing-Remitting (RR), periods of disease activity (SLEDAI/PGA>0) interspersed with periods of disease inactivity (SLEDAI/PGA=0) at 1 or more visits during 1 year; Chronic Active (CA), SLEDAI/PGA scores are >0 for 1 year at all visits. Disease activity at yearly intervals (“1-year blocks”) was readily classified into 1 of the 3 major patterns for each patient. The pattern in each patient of 3 consecutive followup years (“3-year blocks”) was also determined: Persistent Long Quiescent (pLQ), LQ pattern in each of the 3 years; Persistent Remissing-Remitting (pRR), RR pattern in each of the 3 years; Persistent Chronic Active (pCA), CA pattern in each of the 3 years; Mixed, at least 2 different pattern types during 3 consecutive years. The frequency of different pattern groups (LQ, RR, CA) in each “1-year-block” and pattern subgroups (pLQ, pRR, pCA, Mixed) in each “3-year-block” of followup was examined.ResultsThree major patterns of SLE disease activity were identified: LQ, RR, and CA. The RR pattern accounted for the greatest proportion of followup time for both the SLEDAI and PGA, representing 48.3% and 51.8% of total person-years, respectively. The CA pattern was the second most frequent pattern observed (SLEDAI 35.5%, PGA 38.5% of total person-years). The least prevalent pattern was the LQ (SLEDAI 16.1%, PGA 9.5% of total person-years), indicating that 655 patients experienced 1674 LQ “1-year-blocks”, and 352 patients experienced 981 LQ “1-year-blocks”, using SLEDAI and PGA, respectively. When disease activity was defined within 3-year intervals, the Mixed pattern was the most common for both the SLEDAI and LAI, representing 55% of total “3-year blocks”. The pRR and pCA patterns were intermediate and similar in frequency (pRR 19.8%, pCA 20.7%). The pLQ was the least frequent pattern (SLEDAI: 5.7% and PGA: 2.8%). The most common discrepancy between instruments was that the PGA demonstrated CA when the SLEDAI showed an RR pattern. The SLEDAI was more likely to depict the LQ pattern than was the PGA (Table 1.)ConclusionsIn this large cohort, the three major patterns of SLE disease activity as originally identified by Barr et al. were confirmed. In the present study, the RR pattern appeared to be the most prevalent pattern type. Long quiescence was achieved in a subset of patients. Over a 3-year perspective almost half the patient maintained their disease activity pattern.Disclosure of InterestNone declared</description><issn>0003-4967</issn><issn>1468-2060</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqVkE1OwzAQhS0EEqVwB0tdp9h14jhiVbWFIkUqomVtOelEcWl-sB1Qd90gDsANexKSlgVbVjPzNO9p5kNoQMmQUsZvVVmaHJpira03IjTwoNkqM_Q5J2eoR30uWpmTc9QjhDDPj3h4ia6s3bQjEVT00NdyvCJMBIf951RbUBbwOHX6XbsdflLOgSktXryDwStdANZlp2ooncUf2uV4Gc_wYf-NFX4GZypbQ-cGPAWbGl0f-3GptjurLa4y7HLA86p-1W1s3NSNxZMqr4y7RheZ2lq4-a199HI_W03mXrx4eJyMYy-hIog8lQghwmAUAoDPQ5L5KvQFYZzyVqQqA0J9xdIkG6Vr5UeCRQkjAjgjXFEasD4anHJrU701YJ3cVI1pD7SSRoR2UUHUbt2dttL2JWsgk7XRhTI7SYnsyMs_5GVHXh7Jy4586-Ynd1Js_mX8AaJ0kPk</recordid><startdate>201506</startdate><enddate>201506</enddate><creator>Györi, N.</creator><creator>Chatzidionysiou, A.</creator><creator>Magder, L.</creator><creator>van Vollenhoven, R.</creator><creator>Petri, M.</creator><general>BMJ Publishing Group LTD</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88I</scope><scope>8AF</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BTHHO</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9-</scope><scope>K9.</scope><scope>LK8</scope><scope>M0R</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope></search><sort><creationdate>201506</creationdate><title>SAT0385 Disease Activity Patterns Over Time in Patients with SLE – a Retrospective Descriptive Analysis of the Hopkins Lupus Cohort</title><author>Györi, N. ; Chatzidionysiou, A. ; Magder, L. ; van Vollenhoven, R. ; Petri, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b1859-ab8887527eee4670f4a748036165271afe014a3cbf2cda49839b308e6306a1153</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Györi, N.</creatorcontrib><creatorcontrib>Chatzidionysiou, A.</creatorcontrib><creatorcontrib>Magder, L.</creatorcontrib><creatorcontrib>van Vollenhoven, R.</creatorcontrib><creatorcontrib>Petri, M.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>STEM Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>BMJ Journals</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Consumer Health Database (Alumni Edition)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Consumer Health Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><jtitle>Annals of the rheumatic diseases</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Györi, N.</au><au>Chatzidionysiou, A.</au><au>Magder, L.</au><au>van Vollenhoven, R.</au><au>Petri, M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>SAT0385 Disease Activity Patterns Over Time in Patients with SLE – a Retrospective Descriptive Analysis of the Hopkins Lupus Cohort</atitle><jtitle>Annals of the rheumatic diseases</jtitle><date>2015-06</date><risdate>2015</risdate><volume>74</volume><issue>Suppl 2</issue><spage>798</spage><epage>799</epage><pages>798-799</pages><issn>0003-4967</issn><eissn>1468-2060</eissn><coden>ARDIAO</coden><abstract>BackgroundSystemic Lupus Erythematosus (SLE) is a multi-systemic inflammatory disease, characterized by an extreme variability of its expression, both between individuals and within individuals, over time. Overall disease activity appears to be an important predictor of both mortality and organ damage. It is therefore important to understand the burden of disease course over time among patients with SLE (Barr et al. 1999)ObjectivesTo discern and describe SLE disease activity patterns over time by analyzing data from the Hopkins Lupus Cohort.MethodsDisease activity was retrospectively studied in a cohort of 2386 consecutive SLE patients followed up quarterly for 1-28 years (10 367 person-years of followup). SLE disease activity patterns were defined using 1) Physician Global Assessment (PGA) and 2) SLE Disease Activity Index (SLEDAI), including serology: Long Quiescent (LQ), SLEDAI/PGA=0 for 1 year at all visits; Relapsing-Remitting (RR), periods of disease activity (SLEDAI/PGA>0) interspersed with periods of disease inactivity (SLEDAI/PGA=0) at 1 or more visits during 1 year; Chronic Active (CA), SLEDAI/PGA scores are >0 for 1 year at all visits. Disease activity at yearly intervals (“1-year blocks”) was readily classified into 1 of the 3 major patterns for each patient. The pattern in each patient of 3 consecutive followup years (“3-year blocks”) was also determined: Persistent Long Quiescent (pLQ), LQ pattern in each of the 3 years; Persistent Remissing-Remitting (pRR), RR pattern in each of the 3 years; Persistent Chronic Active (pCA), CA pattern in each of the 3 years; Mixed, at least 2 different pattern types during 3 consecutive years. The frequency of different pattern groups (LQ, RR, CA) in each “1-year-block” and pattern subgroups (pLQ, pRR, pCA, Mixed) in each “3-year-block” of followup was examined.ResultsThree major patterns of SLE disease activity were identified: LQ, RR, and CA. The RR pattern accounted for the greatest proportion of followup time for both the SLEDAI and PGA, representing 48.3% and 51.8% of total person-years, respectively. The CA pattern was the second most frequent pattern observed (SLEDAI 35.5%, PGA 38.5% of total person-years). The least prevalent pattern was the LQ (SLEDAI 16.1%, PGA 9.5% of total person-years), indicating that 655 patients experienced 1674 LQ “1-year-blocks”, and 352 patients experienced 981 LQ “1-year-blocks”, using SLEDAI and PGA, respectively. When disease activity was defined within 3-year intervals, the Mixed pattern was the most common for both the SLEDAI and LAI, representing 55% of total “3-year blocks”. The pRR and pCA patterns were intermediate and similar in frequency (pRR 19.8%, pCA 20.7%). The pLQ was the least frequent pattern (SLEDAI: 5.7% and PGA: 2.8%). The most common discrepancy between instruments was that the PGA demonstrated CA when the SLEDAI showed an RR pattern. The SLEDAI was more likely to depict the LQ pattern than was the PGA (Table 1.)ConclusionsIn this large cohort, the three major patterns of SLE disease activity as originally identified by Barr et al. were confirmed. In the present study, the RR pattern appeared to be the most prevalent pattern type. Long quiescence was achieved in a subset of patients. Over a 3-year perspective almost half the patient maintained their disease activity pattern.Disclosure of InterestNone declared</abstract><cop>London</cop><pub>BMJ Publishing Group LTD</pub><doi>10.1136/annrheumdis-2015-eular.4660</doi><tpages>2</tpages></addata></record> |
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title | SAT0385 Disease Activity Patterns Over Time in Patients with SLE – a Retrospective Descriptive Analysis of the Hopkins Lupus Cohort |
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