Building a composite score for patient self-report of flare in osteoarthritis: a comparison of methods with the Flare-OA-16 questionnaire
This study aims to compare methods of constructing a composite score for the Flare-OA-16 self-reported questionnaire. Participants with knee and hip osteoarthritis (OA) completed a validated 16-item questionnaire assessing five domains of flare. Three estimation methods were compared: (i) second-ord...
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| Veröffentlicht in: | Journal of clinical epidemiology 2024-10, Vol.174 (5), p.111467, Article 111467 |
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| creator | Queiroga, Fabiana Epstein, Jonathan Erpelding, Marie-Line Soudant, Marc King, Lauren Spitz, Elisabeth Maillefert, Jean-Francis Fautrel, Bruno Callahan, Leigh F. March, Lyn Hunter, David J. Guillemin, Francis |
| description | This study aims to compare methods of constructing a composite score for the Flare-OA-16 self-reported questionnaire.
Participants with knee and hip osteoarthritis (OA) completed a validated 16-item questionnaire assessing five domains of flare. Three estimation methods were compared: (i) second-order confirmatory factor analysis (CFA); (ii) logistic regression, according to the participant's self-report of flare (yes/no); and (iii) Rasch method, with weighted scores in each dimension. The distribution (floor effect [FF] and ceiling effect [CF]) were described and the known-group validity (by self-reported flare) tested by Wilcoxon rank-sum test. Similarity between the scores was analyzed by intraclass correlation coefficient (ICC) and their performance against self-report compared by areas under ROC curves (AUC). Intrascore test-retest reliability at 14 days was assessed by ICC.
In a sample of 381 participants, 247 reported having a flare. CFA showed fit indices (comparative fit index [CFI] = 0.95; root mean square error of approximation [RMSEA] = 0.08) and estimated composite mean score = 4.33(SD = 2.85) (FF = 14.9%, CF = 0%). For the logistic regression estimation, the mean composite score was 6.48 (SD = 3.13) (FF = 0%; CF = 0%). With Rasch model, the mean composite score was 4.35 (SD = 2.60) (FF = 14.9%; CF = 0%). Similarity analysis indicated a greater concordance between CFA and Rasch scores (ICC = 0.98) than between logistic regression score and the two others (ICC = 0.88 with Rasch score and 0.90 with CFA score). The AUC indicated similar performance of all methods: logistic model (AUC = 0.89 [0.85–0.92]), CFA, and Rasch model (AUC = 0.86 [0.82–0.90]). The difference between groups was significant (P |
| doi_str_mv | 10.1016/j.jclinepi.2024.111467 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_hal_p</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_hal_04687040v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0895435624002233</els_id><sourcerecordid>3085683383</sourcerecordid><originalsourceid>FETCH-LOGICAL-c307t-edfba62c9b7d69e3c0b32335009f5c6bb3ee903227b6f91989fbbe8c00908663</originalsourceid><addsrcrecordid>eNqFkcGO1SAUhonRONerrzAhceMseoXSUurK68RxTG4ym9kTSg-Wpi0V6Bgfwbceau_Mwo0JCQl8_-FwPoQuKTlQQvnH_tDrwU4w20NO8uJAKS149QLtqKhEVtY5fYl2RNRlVrCSX6A3IfSE0IpU5Wt0wWrCq7IgO_Tny2KH1k4_sMLajbMLNgIO2nnAxnk8q2hhijjAYDIPs_MRO4PNoBJgJ-xCBKd87LyNNnw6V1HeBjet4Aixc23Av2zscOwA36zJ7O6YUY5_LhCiddOkrIe36JVRQ4B3532P7m--3l_fZqe7b9-vj6dMM1LFDFrTKJ7ruqlaXgPTpGE5YyUhtSk1bxoGUBOW51XDTU1rUZumAaHTPRGcsz262sp2apCzt6Pyv6VTVt4eT3I9IwUXFSnIA03sh42dvfvbqxxt0DAMagK3BMmIKLlgLK09ev8P2rvFT-kjklHKOS1FUSSKb5T2LgQP5rkDSuTqVfbyyatcvcrNawpenssvzQjtc-xJZAI-bwCk0T1Y8DLoJE5Dm0aro2yd_d8bj2UOt1s</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3116615844</pqid></control><display><type>article</type><title>Building a composite score for patient self-report of flare in osteoarthritis: a comparison of methods with the Flare-OA-16 questionnaire</title><source>Elsevier ScienceDirect Journals</source><source>ProQuest Central UK/Ireland</source><creator>Queiroga, Fabiana ; Epstein, Jonathan ; Erpelding, Marie-Line ; Soudant, Marc ; King, Lauren ; Spitz, Elisabeth ; Maillefert, Jean-Francis ; Fautrel, Bruno ; Callahan, Leigh F. ; March, Lyn ; Hunter, David J. ; Guillemin, Francis</creator><creatorcontrib>Queiroga, Fabiana ; Epstein, Jonathan ; Erpelding, Marie-Line ; Soudant, Marc ; King, Lauren ; Spitz, Elisabeth ; Maillefert, Jean-Francis ; Fautrel, Bruno ; Callahan, Leigh F. ; March, Lyn ; Hunter, David J. ; Guillemin, Francis</creatorcontrib><description>This study aims to compare methods of constructing a composite score for the Flare-OA-16 self-reported questionnaire.
Participants with knee and hip osteoarthritis (OA) completed a validated 16-item questionnaire assessing five domains of flare. Three estimation methods were compared: (i) second-order confirmatory factor analysis (CFA); (ii) logistic regression, according to the participant's self-report of flare (yes/no); and (iii) Rasch method, with weighted scores in each dimension. The distribution (floor effect [FF] and ceiling effect [CF]) were described and the known-group validity (by self-reported flare) tested by Wilcoxon rank-sum test. Similarity between the scores was analyzed by intraclass correlation coefficient (ICC) and their performance against self-report compared by areas under ROC curves (AUC). Intrascore test-retest reliability at 14 days was assessed by ICC.
In a sample of 381 participants, 247 reported having a flare. CFA showed fit indices (comparative fit index [CFI] = 0.95; root mean square error of approximation [RMSEA] = 0.08) and estimated composite mean score = 4.33(SD = 2.85) (FF = 14.9%, CF = 0%). For the logistic regression estimation, the mean composite score was 6.48 (SD = 3.13) (FF = 0%; CF = 0%). With Rasch model, the mean composite score was 4.35 (SD = 2.60) (FF = 14.9%; CF = 0%). Similarity analysis indicated a greater concordance between CFA and Rasch scores (ICC = 0.98) than between logistic regression score and the two others (ICC = 0.88 with Rasch score and 0.90 with CFA score). The AUC indicated similar performance of all methods: logistic model (AUC = 0.89 [0.85–0.92]), CFA, and Rasch model (AUC = 0.86 [0.82–0.90]). The difference between groups was significant (P < .05) for scores estimated by CFA (3.98), Rasch model (4.95), and logistic regression (4.30). The reproducibility was ICC = 0.84 (0.75–0.90) for Rasch and CFA scores and ICC = 0.78(0.66–86) for logistic model.
Three alternatives explored to build a composite score showed similar construct validity. Some metric superiority (better score distribution and reproducibility) of the Rasch model is promising for the detection of occurrence and assessment of severity of a flare in OA.
[Display omitted]
•A score to assess the occurrence and severity of flares of knee or hip osteoarthritis (OA) would help guide interventions.•Three estimation methods to obtain a composite score for the Flare-OA-16 self-reported questionnaire were compared: second-order confirmatory factor analysis, logistic regression, and Rasch model.•The three methods showed similar performance in predicting self-reported flare but a better scale distribution was in favor of the Rasch model.</description><identifier>ISSN: 0895-4356</identifier><identifier>ISSN: 1878-5921</identifier><identifier>EISSN: 1878-5921</identifier><identifier>DOI: 10.1016/j.jclinepi.2024.111467</identifier><identifier>PMID: 39067540</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Composite score ; Confirmatory factor analysis ; Correlation coefficient ; Correlation coefficients ; Decision making ; Factor analysis ; Flare ; Hip joint ; Human health and pathology ; Knee ; Life Sciences ; Logistic regression ; Logit models ; Maximum likelihood method ; Osteoarthritis ; Patients ; Psychological aspects ; Questionnaire ; Questionnaires ; Rasch model ; Regression analysis ; Regression models ; Reproducibility ; Rheumatology ; Self report ; Similarity ; Software</subject><ispartof>Journal of clinical epidemiology, 2024-10, Vol.174 (5), p.111467, Article 111467</ispartof><rights>2024 The Authors</rights><rights>Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.</rights><rights>2024. The Authors</rights><rights>Attribution - NonCommercial - NoDerivatives</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c307t-edfba62c9b7d69e3c0b32335009f5c6bb3ee903227b6f91989fbbe8c00908663</cites><orcidid>0000-0002-9860-7024 ; 0000-0001-5814-6924 ; 0000-0002-3811-8202 ; 0000-0001-7436-1974</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/3116615844?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>230,314,778,782,883,3539,27907,27908,45978,64366,64368,64370,72220</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39067540$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.science/hal-04687040$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Queiroga, Fabiana</creatorcontrib><creatorcontrib>Epstein, Jonathan</creatorcontrib><creatorcontrib>Erpelding, Marie-Line</creatorcontrib><creatorcontrib>Soudant, Marc</creatorcontrib><creatorcontrib>King, Lauren</creatorcontrib><creatorcontrib>Spitz, Elisabeth</creatorcontrib><creatorcontrib>Maillefert, Jean-Francis</creatorcontrib><creatorcontrib>Fautrel, Bruno</creatorcontrib><creatorcontrib>Callahan, Leigh F.</creatorcontrib><creatorcontrib>March, Lyn</creatorcontrib><creatorcontrib>Hunter, David J.</creatorcontrib><creatorcontrib>Guillemin, Francis</creatorcontrib><title>Building a composite score for patient self-report of flare in osteoarthritis: a comparison of methods with the Flare-OA-16 questionnaire</title><title>Journal of clinical epidemiology</title><addtitle>J Clin Epidemiol</addtitle><description>This study aims to compare methods of constructing a composite score for the Flare-OA-16 self-reported questionnaire.
Participants with knee and hip osteoarthritis (OA) completed a validated 16-item questionnaire assessing five domains of flare. Three estimation methods were compared: (i) second-order confirmatory factor analysis (CFA); (ii) logistic regression, according to the participant's self-report of flare (yes/no); and (iii) Rasch method, with weighted scores in each dimension. The distribution (floor effect [FF] and ceiling effect [CF]) were described and the known-group validity (by self-reported flare) tested by Wilcoxon rank-sum test. Similarity between the scores was analyzed by intraclass correlation coefficient (ICC) and their performance against self-report compared by areas under ROC curves (AUC). Intrascore test-retest reliability at 14 days was assessed by ICC.
In a sample of 381 participants, 247 reported having a flare. CFA showed fit indices (comparative fit index [CFI] = 0.95; root mean square error of approximation [RMSEA] = 0.08) and estimated composite mean score = 4.33(SD = 2.85) (FF = 14.9%, CF = 0%). For the logistic regression estimation, the mean composite score was 6.48 (SD = 3.13) (FF = 0%; CF = 0%). With Rasch model, the mean composite score was 4.35 (SD = 2.60) (FF = 14.9%; CF = 0%). Similarity analysis indicated a greater concordance between CFA and Rasch scores (ICC = 0.98) than between logistic regression score and the two others (ICC = 0.88 with Rasch score and 0.90 with CFA score). The AUC indicated similar performance of all methods: logistic model (AUC = 0.89 [0.85–0.92]), CFA, and Rasch model (AUC = 0.86 [0.82–0.90]). The difference between groups was significant (P < .05) for scores estimated by CFA (3.98), Rasch model (4.95), and logistic regression (4.30). The reproducibility was ICC = 0.84 (0.75–0.90) for Rasch and CFA scores and ICC = 0.78(0.66–86) for logistic model.
Three alternatives explored to build a composite score showed similar construct validity. Some metric superiority (better score distribution and reproducibility) of the Rasch model is promising for the detection of occurrence and assessment of severity of a flare in OA.
[Display omitted]
•A score to assess the occurrence and severity of flares of knee or hip osteoarthritis (OA) would help guide interventions.•Three estimation methods to obtain a composite score for the Flare-OA-16 self-reported questionnaire were compared: second-order confirmatory factor analysis, logistic regression, and Rasch model.•The three methods showed similar performance in predicting self-reported flare but a better scale distribution was in favor of the Rasch model.</description><subject>Composite score</subject><subject>Confirmatory factor analysis</subject><subject>Correlation coefficient</subject><subject>Correlation coefficients</subject><subject>Decision making</subject><subject>Factor analysis</subject><subject>Flare</subject><subject>Hip joint</subject><subject>Human health and pathology</subject><subject>Knee</subject><subject>Life Sciences</subject><subject>Logistic regression</subject><subject>Logit models</subject><subject>Maximum likelihood method</subject><subject>Osteoarthritis</subject><subject>Patients</subject><subject>Psychological aspects</subject><subject>Questionnaire</subject><subject>Questionnaires</subject><subject>Rasch model</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Reproducibility</subject><subject>Rheumatology</subject><subject>Self report</subject><subject>Similarity</subject><subject>Software</subject><issn>0895-4356</issn><issn>1878-5921</issn><issn>1878-5921</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqFkcGO1SAUhonRONerrzAhceMseoXSUurK68RxTG4ym9kTSg-Wpi0V6Bgfwbceau_Mwo0JCQl8_-FwPoQuKTlQQvnH_tDrwU4w20NO8uJAKS149QLtqKhEVtY5fYl2RNRlVrCSX6A3IfSE0IpU5Wt0wWrCq7IgO_Tny2KH1k4_sMLajbMLNgIO2nnAxnk8q2hhijjAYDIPs_MRO4PNoBJgJ-xCBKd87LyNNnw6V1HeBjet4Aixc23Av2zscOwA36zJ7O6YUY5_LhCiddOkrIe36JVRQ4B3532P7m--3l_fZqe7b9-vj6dMM1LFDFrTKJ7ruqlaXgPTpGE5YyUhtSk1bxoGUBOW51XDTU1rUZumAaHTPRGcsz262sp2apCzt6Pyv6VTVt4eT3I9IwUXFSnIA03sh42dvfvbqxxt0DAMagK3BMmIKLlgLK09ev8P2rvFT-kjklHKOS1FUSSKb5T2LgQP5rkDSuTqVfbyyatcvcrNawpenssvzQjtc-xJZAI-bwCk0T1Y8DLoJE5Dm0aro2yd_d8bj2UOt1s</recordid><startdate>20241001</startdate><enddate>20241001</enddate><creator>Queiroga, Fabiana</creator><creator>Epstein, Jonathan</creator><creator>Erpelding, Marie-Line</creator><creator>Soudant, Marc</creator><creator>King, Lauren</creator><creator>Spitz, Elisabeth</creator><creator>Maillefert, Jean-Francis</creator><creator>Fautrel, Bruno</creator><creator>Callahan, Leigh F.</creator><creator>March, Lyn</creator><creator>Hunter, David J.</creator><creator>Guillemin, Francis</creator><general>Elsevier Inc</general><general>Elsevier 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a composite score for patient self-report of flare in osteoarthritis: a comparison of methods with the Flare-OA-16 questionnaire</title><author>Queiroga, Fabiana ; Epstein, Jonathan ; Erpelding, Marie-Line ; Soudant, Marc ; King, Lauren ; Spitz, Elisabeth ; Maillefert, Jean-Francis ; Fautrel, Bruno ; Callahan, Leigh F. ; March, Lyn ; Hunter, David J. ; Guillemin, Francis</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c307t-edfba62c9b7d69e3c0b32335009f5c6bb3ee903227b6f91989fbbe8c00908663</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Composite score</topic><topic>Confirmatory factor analysis</topic><topic>Correlation coefficient</topic><topic>Correlation coefficients</topic><topic>Decision making</topic><topic>Factor analysis</topic><topic>Flare</topic><topic>Hip joint</topic><topic>Human health and pathology</topic><topic>Knee</topic><topic>Life Sciences</topic><topic>Logistic regression</topic><topic>Logit models</topic><topic>Maximum likelihood method</topic><topic>Osteoarthritis</topic><topic>Patients</topic><topic>Psychological aspects</topic><topic>Questionnaire</topic><topic>Questionnaires</topic><topic>Rasch model</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Reproducibility</topic><topic>Rheumatology</topic><topic>Self report</topic><topic>Similarity</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Queiroga, Fabiana</creatorcontrib><creatorcontrib>Epstein, Jonathan</creatorcontrib><creatorcontrib>Erpelding, Marie-Line</creatorcontrib><creatorcontrib>Soudant, Marc</creatorcontrib><creatorcontrib>King, Lauren</creatorcontrib><creatorcontrib>Spitz, Elisabeth</creatorcontrib><creatorcontrib>Maillefert, Jean-Francis</creatorcontrib><creatorcontrib>Fautrel, Bruno</creatorcontrib><creatorcontrib>Callahan, Leigh 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Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>Journal of clinical epidemiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Queiroga, Fabiana</au><au>Epstein, Jonathan</au><au>Erpelding, Marie-Line</au><au>Soudant, Marc</au><au>King, Lauren</au><au>Spitz, Elisabeth</au><au>Maillefert, Jean-Francis</au><au>Fautrel, Bruno</au><au>Callahan, Leigh F.</au><au>March, Lyn</au><au>Hunter, David J.</au><au>Guillemin, Francis</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Building a composite score for patient self-report of flare in osteoarthritis: a comparison of methods with the Flare-OA-16 questionnaire</atitle><jtitle>Journal of clinical epidemiology</jtitle><addtitle>J Clin Epidemiol</addtitle><date>2024-10-01</date><risdate>2024</risdate><volume>174</volume><issue>5</issue><spage>111467</spage><pages>111467-</pages><artnum>111467</artnum><issn>0895-4356</issn><issn>1878-5921</issn><eissn>1878-5921</eissn><abstract>This study aims to compare methods of constructing a composite score for the Flare-OA-16 self-reported questionnaire.
Participants with knee and hip osteoarthritis (OA) completed a validated 16-item questionnaire assessing five domains of flare. Three estimation methods were compared: (i) second-order confirmatory factor analysis (CFA); (ii) logistic regression, according to the participant's self-report of flare (yes/no); and (iii) Rasch method, with weighted scores in each dimension. The distribution (floor effect [FF] and ceiling effect [CF]) were described and the known-group validity (by self-reported flare) tested by Wilcoxon rank-sum test. Similarity between the scores was analyzed by intraclass correlation coefficient (ICC) and their performance against self-report compared by areas under ROC curves (AUC). Intrascore test-retest reliability at 14 days was assessed by ICC.
In a sample of 381 participants, 247 reported having a flare. CFA showed fit indices (comparative fit index [CFI] = 0.95; root mean square error of approximation [RMSEA] = 0.08) and estimated composite mean score = 4.33(SD = 2.85) (FF = 14.9%, CF = 0%). For the logistic regression estimation, the mean composite score was 6.48 (SD = 3.13) (FF = 0%; CF = 0%). With Rasch model, the mean composite score was 4.35 (SD = 2.60) (FF = 14.9%; CF = 0%). Similarity analysis indicated a greater concordance between CFA and Rasch scores (ICC = 0.98) than between logistic regression score and the two others (ICC = 0.88 with Rasch score and 0.90 with CFA score). The AUC indicated similar performance of all methods: logistic model (AUC = 0.89 [0.85–0.92]), CFA, and Rasch model (AUC = 0.86 [0.82–0.90]). The difference between groups was significant (P < .05) for scores estimated by CFA (3.98), Rasch model (4.95), and logistic regression (4.30). The reproducibility was ICC = 0.84 (0.75–0.90) for Rasch and CFA scores and ICC = 0.78(0.66–86) for logistic model.
Three alternatives explored to build a composite score showed similar construct validity. Some metric superiority (better score distribution and reproducibility) of the Rasch model is promising for the detection of occurrence and assessment of severity of a flare in OA.
[Display omitted]
•A score to assess the occurrence and severity of flares of knee or hip osteoarthritis (OA) would help guide interventions.•Three estimation methods to obtain a composite score for the Flare-OA-16 self-reported questionnaire were compared: second-order confirmatory factor analysis, logistic regression, and Rasch model.•The three methods showed similar performance in predicting self-reported flare but a better scale distribution was in favor of the Rasch model.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>39067540</pmid><doi>10.1016/j.jclinepi.2024.111467</doi><orcidid>https://orcid.org/0000-0002-9860-7024</orcidid><orcidid>https://orcid.org/0000-0001-5814-6924</orcidid><orcidid>https://orcid.org/0000-0002-3811-8202</orcidid><orcidid>https://orcid.org/0000-0001-7436-1974</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Journal of clinical epidemiology, 2024-10, Vol.174 (5), p.111467, Article 111467 |
| issn | 0895-4356 1878-5921 1878-5921 |
| language | eng |
| recordid | cdi_hal_primary_oai_HAL_hal_04687040v1 |
| source | Elsevier ScienceDirect Journals; ProQuest Central UK/Ireland |
| subjects | Composite score Confirmatory factor analysis Correlation coefficient Correlation coefficients Decision making Factor analysis Flare Hip joint Human health and pathology Knee Life Sciences Logistic regression Logit models Maximum likelihood method Osteoarthritis Patients Psychological aspects Questionnaire Questionnaires Rasch model Regression analysis Regression models Reproducibility Rheumatology Self report Similarity Software |
| title | Building a composite score for patient self-report of flare in osteoarthritis: a comparison of methods with the Flare-OA-16 questionnaire |
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