A search to the target tissue in which RA-specific inflammation starts: a detailed MRI study to improve identification of RA-specific features in the phase of clinically suspect arthralgia

Objective Based on a unique cohort of clinically suspect arthralgia (CSA) patients, we analysed which combinations of MRI features at onset were predictive for rheumatoid arthritis (RA) development. This was done to increase our comprehension of locations of RA onset and improve the predictive accuracy of MRI in CSA. Methods In the discovery cohort, 225 CSA patients were followed on clinical arthritis development. Contrast-enhanced 1.5 T MRIs were made of unilateral metacarpophalangeal (MCP) (2–5), wrist, and metatarsophalangeal (1–5) joints at baseline and scored for synovitis, tenosynovitis, and bone marrow edema. Severity, number, and combinations of locations (joint/tendon/bone) with subclinical inflammation were determined, with symptom-free controls of similar age category as reference. Cox regression was used for predictor selection. Predictive values were determined at 1 year follow-up. Results were validated in 209 CSA patients. Results In both cohorts, 15% developed arthritis < 1 year. The multivariable Cox model selected presence of MCP-extensor peritendinitis (HR 4.38 (2.07–9.25)) and the number of locations with subclinical inflammation (1–2 locations HR 2.54 (1.11–5.82); ≥ 3 locations HR 3.75 (1.49–9.48)) as predictors. Severity and combinations of inflammatory lesions were not selected. Based on these variables, five risk categories were defined: no subclinical inflammation, 1–2 locations, or ≥ 3 locations, with or without MCP-extensor peritendinitis. Positive predictive values (PPVs) ranged 5% (lowest category; NPV 95%) to 67% (highest category). Similar findings were obtained in the validation cohort; PPVs ranged 4% (lowest category; NPV 96%) to 63% (highest category). Conclusion Tenosynovitis, particularly MCP-extensor peritendinitis, is among the first tissues affected by RA. Incorporating this feature and number of locations with subclinical inflammation improved prediction making with PPVs up to 63–67%. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Matthijssen, Xanthe M. E. [verfasserIn] Wouters, Fenne Boeters, Debbie M. Boer, Aleid C. Dakkak, Yousra J. Niemantsverdriet, Ellis van der Helm-van Mil, Annette H. M.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Rheumatoid arthritis MRI Biomarkers Cohort study Risk factors

Anmerkung:	© The Author(s). 2019

Übergeordnetes Werk:	Enthalten in: Arthritis Research & Therapy - London : BioMed Central, 1999, 21(2019), 1 vom: 27. Nov.
Übergeordnetes Werk:	volume:21 ; year:2019 ; number:1 ; day:27 ; month:11

Links:	Volltext

DOI / URN:	10.1186/s13075-019-2002-z

Katalog-ID:	SPR030231965

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520			\|a Objective Based on a unique cohort of clinically suspect arthralgia (CSA) patients, we analysed which combinations of MRI features at onset were predictive for rheumatoid arthritis (RA) development. This was done to increase our comprehension of locations of RA onset and improve the predictive accuracy of MRI in CSA. Methods In the discovery cohort, 225 CSA patients were followed on clinical arthritis development. Contrast-enhanced 1.5 T MRIs were made of unilateral metacarpophalangeal (MCP) (2–5), wrist, and metatarsophalangeal (1–5) joints at baseline and scored for synovitis, tenosynovitis, and bone marrow edema. Severity, number, and combinations of locations (joint/tendon/bone) with subclinical inflammation were determined, with symptom-free controls of similar age category as reference. Cox regression was used for predictor selection. Predictive values were determined at 1 year follow-up. Results were validated in 209 CSA patients. Results In both cohorts, 15% developed arthritis < 1 year. The multivariable Cox model selected presence of MCP-extensor peritendinitis (HR 4.38 (2.07–9.25)) and the number of locations with subclinical inflammation (1–2 locations HR 2.54 (1.11–5.82); ≥ 3 locations HR 3.75 (1.49–9.48)) as predictors. Severity and combinations of inflammatory lesions were not selected. Based on these variables, five risk categories were defined: no subclinical inflammation, 1–2 locations, or ≥ 3 locations, with or without MCP-extensor peritendinitis. Positive predictive values (PPVs) ranged 5% (lowest category; NPV 95%) to 67% (highest category). Similar findings were obtained in the validation cohort; PPVs ranged 4% (lowest category; NPV 96%) to 63% (highest category). Conclusion Tenosynovitis, particularly MCP-extensor peritendinitis, is among the first tissues affected by RA. Incorporating this feature and number of locations with subclinical inflammation improved prediction making with PPVs up to 63–67%.
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allfields	10.1186/s13075-019-2002-z doi (DE-627)SPR030231965 (SPR)s13075-019-2002-z-e DE-627 ger DE-627 rakwb eng Matthijssen, Xanthe M. E. verfasserin (orcid)0000-0001-7332-8072 aut A search to the target tissue in which RA-specific inflammation starts: a detailed MRI study to improve identification of RA-specific features in the phase of clinically suspect arthralgia 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Objective Based on a unique cohort of clinically suspect arthralgia (CSA) patients, we analysed which combinations of MRI features at onset were predictive for rheumatoid arthritis (RA) development. This was done to increase our comprehension of locations of RA onset and improve the predictive accuracy of MRI in CSA. Methods In the discovery cohort, 225 CSA patients were followed on clinical arthritis development. Contrast-enhanced 1.5 T MRIs were made of unilateral metacarpophalangeal (MCP) (2–5), wrist, and metatarsophalangeal (1–5) joints at baseline and scored for synovitis, tenosynovitis, and bone marrow edema. Severity, number, and combinations of locations (joint/tendon/bone) with subclinical inflammation were determined, with symptom-free controls of similar age category as reference. Cox regression was used for predictor selection. Predictive values were determined at 1 year follow-up. Results were validated in 209 CSA patients. Results In both cohorts, 15% developed arthritis < 1 year. The multivariable Cox model selected presence of MCP-extensor peritendinitis (HR 4.38 (2.07–9.25)) and the number of locations with subclinical inflammation (1–2 locations HR 2.54 (1.11–5.82); ≥ 3 locations HR 3.75 (1.49–9.48)) as predictors. Severity and combinations of inflammatory lesions were not selected. Based on these variables, five risk categories were defined: no subclinical inflammation, 1–2 locations, or ≥ 3 locations, with or without MCP-extensor peritendinitis. Positive predictive values (PPVs) ranged 5% (lowest category; NPV 95%) to 67% (highest category). Similar findings were obtained in the validation cohort; PPVs ranged 4% (lowest category; NPV 96%) to 63% (highest category). Conclusion Tenosynovitis, particularly MCP-extensor peritendinitis, is among the first tissues affected by RA. Incorporating this feature and number of locations with subclinical inflammation improved prediction making with PPVs up to 63–67%. Rheumatoid arthritis (dpeaa)DE-He213 MRI (dpeaa)DE-He213 Biomarkers (dpeaa)DE-He213 Cohort study (dpeaa)DE-He213 Risk factors (dpeaa)DE-He213 Wouters, Fenne aut Boeters, Debbie M. aut Boer, Aleid C. aut Dakkak, Yousra J. aut Niemantsverdriet, Ellis aut van der Helm-van Mil, Annette H. M. aut Enthalten in Arthritis Research & Therapy London : BioMed Central, 1999 21(2019), 1 vom: 27. Nov. (DE-627)326646418 (DE-600)2041668-4 1478-6354 nnns volume:21 year:2019 number:1 day:27 month:11 https://dx.doi.org/10.1186/s13075-019-2002-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 21 2019 1 27 11
spelling	10.1186/s13075-019-2002-z doi (DE-627)SPR030231965 (SPR)s13075-019-2002-z-e DE-627 ger DE-627 rakwb eng Matthijssen, Xanthe M. E. verfasserin (orcid)0000-0001-7332-8072 aut A search to the target tissue in which RA-specific inflammation starts: a detailed MRI study to improve identification of RA-specific features in the phase of clinically suspect arthralgia 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Objective Based on a unique cohort of clinically suspect arthralgia (CSA) patients, we analysed which combinations of MRI features at onset were predictive for rheumatoid arthritis (RA) development. This was done to increase our comprehension of locations of RA onset and improve the predictive accuracy of MRI in CSA. Methods In the discovery cohort, 225 CSA patients were followed on clinical arthritis development. Contrast-enhanced 1.5 T MRIs were made of unilateral metacarpophalangeal (MCP) (2–5), wrist, and metatarsophalangeal (1–5) joints at baseline and scored for synovitis, tenosynovitis, and bone marrow edema. Severity, number, and combinations of locations (joint/tendon/bone) with subclinical inflammation were determined, with symptom-free controls of similar age category as reference. Cox regression was used for predictor selection. Predictive values were determined at 1 year follow-up. Results were validated in 209 CSA patients. Results In both cohorts, 15% developed arthritis < 1 year. The multivariable Cox model selected presence of MCP-extensor peritendinitis (HR 4.38 (2.07–9.25)) and the number of locations with subclinical inflammation (1–2 locations HR 2.54 (1.11–5.82); ≥ 3 locations HR 3.75 (1.49–9.48)) as predictors. Severity and combinations of inflammatory lesions were not selected. Based on these variables, five risk categories were defined: no subclinical inflammation, 1–2 locations, or ≥ 3 locations, with or without MCP-extensor peritendinitis. Positive predictive values (PPVs) ranged 5% (lowest category; NPV 95%) to 67% (highest category). Similar findings were obtained in the validation cohort; PPVs ranged 4% (lowest category; NPV 96%) to 63% (highest category). Conclusion Tenosynovitis, particularly MCP-extensor peritendinitis, is among the first tissues affected by RA. Incorporating this feature and number of locations with subclinical inflammation improved prediction making with PPVs up to 63–67%. Rheumatoid arthritis (dpeaa)DE-He213 MRI (dpeaa)DE-He213 Biomarkers (dpeaa)DE-He213 Cohort study (dpeaa)DE-He213 Risk factors (dpeaa)DE-He213 Wouters, Fenne aut Boeters, Debbie M. aut Boer, Aleid C. aut Dakkak, Yousra J. aut Niemantsverdriet, Ellis aut van der Helm-van Mil, Annette H. M. aut Enthalten in Arthritis Research & Therapy London : BioMed Central, 1999 21(2019), 1 vom: 27. Nov. (DE-627)326646418 (DE-600)2041668-4 1478-6354 nnns volume:21 year:2019 number:1 day:27 month:11 https://dx.doi.org/10.1186/s13075-019-2002-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 21 2019 1 27 11
allfields_unstemmed	10.1186/s13075-019-2002-z doi (DE-627)SPR030231965 (SPR)s13075-019-2002-z-e DE-627 ger DE-627 rakwb eng Matthijssen, Xanthe M. E. verfasserin (orcid)0000-0001-7332-8072 aut A search to the target tissue in which RA-specific inflammation starts: a detailed MRI study to improve identification of RA-specific features in the phase of clinically suspect arthralgia 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Objective Based on a unique cohort of clinically suspect arthralgia (CSA) patients, we analysed which combinations of MRI features at onset were predictive for rheumatoid arthritis (RA) development. This was done to increase our comprehension of locations of RA onset and improve the predictive accuracy of MRI in CSA. Methods In the discovery cohort, 225 CSA patients were followed on clinical arthritis development. Contrast-enhanced 1.5 T MRIs were made of unilateral metacarpophalangeal (MCP) (2–5), wrist, and metatarsophalangeal (1–5) joints at baseline and scored for synovitis, tenosynovitis, and bone marrow edema. Severity, number, and combinations of locations (joint/tendon/bone) with subclinical inflammation were determined, with symptom-free controls of similar age category as reference. Cox regression was used for predictor selection. Predictive values were determined at 1 year follow-up. Results were validated in 209 CSA patients. Results In both cohorts, 15% developed arthritis < 1 year. The multivariable Cox model selected presence of MCP-extensor peritendinitis (HR 4.38 (2.07–9.25)) and the number of locations with subclinical inflammation (1–2 locations HR 2.54 (1.11–5.82); ≥ 3 locations HR 3.75 (1.49–9.48)) as predictors. Severity and combinations of inflammatory lesions were not selected. Based on these variables, five risk categories were defined: no subclinical inflammation, 1–2 locations, or ≥ 3 locations, with or without MCP-extensor peritendinitis. Positive predictive values (PPVs) ranged 5% (lowest category; NPV 95%) to 67% (highest category). Similar findings were obtained in the validation cohort; PPVs ranged 4% (lowest category; NPV 96%) to 63% (highest category). Conclusion Tenosynovitis, particularly MCP-extensor peritendinitis, is among the first tissues affected by RA. Incorporating this feature and number of locations with subclinical inflammation improved prediction making with PPVs up to 63–67%. Rheumatoid arthritis (dpeaa)DE-He213 MRI (dpeaa)DE-He213 Biomarkers (dpeaa)DE-He213 Cohort study (dpeaa)DE-He213 Risk factors (dpeaa)DE-He213 Wouters, Fenne aut Boeters, Debbie M. aut Boer, Aleid C. aut Dakkak, Yousra J. aut Niemantsverdriet, Ellis aut van der Helm-van Mil, Annette H. M. aut Enthalten in Arthritis Research & Therapy London : BioMed Central, 1999 21(2019), 1 vom: 27. Nov. (DE-627)326646418 (DE-600)2041668-4 1478-6354 nnns volume:21 year:2019 number:1 day:27 month:11 https://dx.doi.org/10.1186/s13075-019-2002-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 21 2019 1 27 11
allfieldsGer	10.1186/s13075-019-2002-z doi (DE-627)SPR030231965 (SPR)s13075-019-2002-z-e DE-627 ger DE-627 rakwb eng Matthijssen, Xanthe M. E. verfasserin (orcid)0000-0001-7332-8072 aut A search to the target tissue in which RA-specific inflammation starts: a detailed MRI study to improve identification of RA-specific features in the phase of clinically suspect arthralgia 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Objective Based on a unique cohort of clinically suspect arthralgia (CSA) patients, we analysed which combinations of MRI features at onset were predictive for rheumatoid arthritis (RA) development. This was done to increase our comprehension of locations of RA onset and improve the predictive accuracy of MRI in CSA. Methods In the discovery cohort, 225 CSA patients were followed on clinical arthritis development. Contrast-enhanced 1.5 T MRIs were made of unilateral metacarpophalangeal (MCP) (2–5), wrist, and metatarsophalangeal (1–5) joints at baseline and scored for synovitis, tenosynovitis, and bone marrow edema. Severity, number, and combinations of locations (joint/tendon/bone) with subclinical inflammation were determined, with symptom-free controls of similar age category as reference. Cox regression was used for predictor selection. Predictive values were determined at 1 year follow-up. Results were validated in 209 CSA patients. Results In both cohorts, 15% developed arthritis < 1 year. The multivariable Cox model selected presence of MCP-extensor peritendinitis (HR 4.38 (2.07–9.25)) and the number of locations with subclinical inflammation (1–2 locations HR 2.54 (1.11–5.82); ≥ 3 locations HR 3.75 (1.49–9.48)) as predictors. Severity and combinations of inflammatory lesions were not selected. Based on these variables, five risk categories were defined: no subclinical inflammation, 1–2 locations, or ≥ 3 locations, with or without MCP-extensor peritendinitis. Positive predictive values (PPVs) ranged 5% (lowest category; NPV 95%) to 67% (highest category). Similar findings were obtained in the validation cohort; PPVs ranged 4% (lowest category; NPV 96%) to 63% (highest category). Conclusion Tenosynovitis, particularly MCP-extensor peritendinitis, is among the first tissues affected by RA. Incorporating this feature and number of locations with subclinical inflammation improved prediction making with PPVs up to 63–67%. Rheumatoid arthritis (dpeaa)DE-He213 MRI (dpeaa)DE-He213 Biomarkers (dpeaa)DE-He213 Cohort study (dpeaa)DE-He213 Risk factors (dpeaa)DE-He213 Wouters, Fenne aut Boeters, Debbie M. aut Boer, Aleid C. aut Dakkak, Yousra J. aut Niemantsverdriet, Ellis aut van der Helm-van Mil, Annette H. M. aut Enthalten in Arthritis Research & Therapy London : BioMed Central, 1999 21(2019), 1 vom: 27. Nov. (DE-627)326646418 (DE-600)2041668-4 1478-6354 nnns volume:21 year:2019 number:1 day:27 month:11 https://dx.doi.org/10.1186/s13075-019-2002-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 21 2019 1 27 11
allfieldsSound	10.1186/s13075-019-2002-z doi (DE-627)SPR030231965 (SPR)s13075-019-2002-z-e DE-627 ger DE-627 rakwb eng Matthijssen, Xanthe M. E. verfasserin (orcid)0000-0001-7332-8072 aut A search to the target tissue in which RA-specific inflammation starts: a detailed MRI study to improve identification of RA-specific features in the phase of clinically suspect arthralgia 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Objective Based on a unique cohort of clinically suspect arthralgia (CSA) patients, we analysed which combinations of MRI features at onset were predictive for rheumatoid arthritis (RA) development. This was done to increase our comprehension of locations of RA onset and improve the predictive accuracy of MRI in CSA. Methods In the discovery cohort, 225 CSA patients were followed on clinical arthritis development. Contrast-enhanced 1.5 T MRIs were made of unilateral metacarpophalangeal (MCP) (2–5), wrist, and metatarsophalangeal (1–5) joints at baseline and scored for synovitis, tenosynovitis, and bone marrow edema. Severity, number, and combinations of locations (joint/tendon/bone) with subclinical inflammation were determined, with symptom-free controls of similar age category as reference. Cox regression was used for predictor selection. Predictive values were determined at 1 year follow-up. Results were validated in 209 CSA patients. Results In both cohorts, 15% developed arthritis < 1 year. The multivariable Cox model selected presence of MCP-extensor peritendinitis (HR 4.38 (2.07–9.25)) and the number of locations with subclinical inflammation (1–2 locations HR 2.54 (1.11–5.82); ≥ 3 locations HR 3.75 (1.49–9.48)) as predictors. Severity and combinations of inflammatory lesions were not selected. Based on these variables, five risk categories were defined: no subclinical inflammation, 1–2 locations, or ≥ 3 locations, with or without MCP-extensor peritendinitis. Positive predictive values (PPVs) ranged 5% (lowest category; NPV 95%) to 67% (highest category). Similar findings were obtained in the validation cohort; PPVs ranged 4% (lowest category; NPV 96%) to 63% (highest category). Conclusion Tenosynovitis, particularly MCP-extensor peritendinitis, is among the first tissues affected by RA. Incorporating this feature and number of locations with subclinical inflammation improved prediction making with PPVs up to 63–67%. Rheumatoid arthritis (dpeaa)DE-He213 MRI (dpeaa)DE-He213 Biomarkers (dpeaa)DE-He213 Cohort study (dpeaa)DE-He213 Risk factors (dpeaa)DE-He213 Wouters, Fenne aut Boeters, Debbie M. aut Boer, Aleid C. aut Dakkak, Yousra J. aut Niemantsverdriet, Ellis aut van der Helm-van Mil, Annette H. M. aut Enthalten in Arthritis Research & Therapy London : BioMed Central, 1999 21(2019), 1 vom: 27. Nov. (DE-627)326646418 (DE-600)2041668-4 1478-6354 nnns volume:21 year:2019 number:1 day:27 month:11 https://dx.doi.org/10.1186/s13075-019-2002-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 21 2019 1 27 11
language	English
source	Enthalten in Arthritis Research & Therapy 21(2019), 1 vom: 27. Nov. volume:21 year:2019 number:1 day:27 month:11
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author	Matthijssen, Xanthe M. E.
spellingShingle	Matthijssen, Xanthe M. E. misc Rheumatoid arthritis misc MRI misc Biomarkers misc Cohort study misc Risk factors A search to the target tissue in which RA-specific inflammation starts: a detailed MRI study to improve identification of RA-specific features in the phase of clinically suspect arthralgia
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topic_title	A search to the target tissue in which RA-specific inflammation starts: a detailed MRI study to improve identification of RA-specific features in the phase of clinically suspect arthralgia Rheumatoid arthritis (dpeaa)DE-He213 MRI (dpeaa)DE-He213 Biomarkers (dpeaa)DE-He213 Cohort study (dpeaa)DE-He213 Risk factors (dpeaa)DE-He213
topic	misc Rheumatoid arthritis misc MRI misc Biomarkers misc Cohort study misc Risk factors
topic_unstemmed	misc Rheumatoid arthritis misc MRI misc Biomarkers misc Cohort study misc Risk factors
topic_browse	misc Rheumatoid arthritis misc MRI misc Biomarkers misc Cohort study misc Risk factors
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title	A search to the target tissue in which RA-specific inflammation starts: a detailed MRI study to improve identification of RA-specific features in the phase of clinically suspect arthralgia
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title_full	A search to the target tissue in which RA-specific inflammation starts: a detailed MRI study to improve identification of RA-specific features in the phase of clinically suspect arthralgia
author_sort	Matthijssen, Xanthe M. E.
journal	Arthritis Research & Therapy
journalStr	Arthritis Research & Therapy
lang_code	eng
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author_browse	Matthijssen, Xanthe M. E. Wouters, Fenne Boeters, Debbie M. Boer, Aleid C. Dakkak, Yousra J. Niemantsverdriet, Ellis van der Helm-van Mil, Annette H. M.
container_volume	21
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author-letter	Matthijssen, Xanthe M. E.
doi_str_mv	10.1186/s13075-019-2002-z
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title_sort	search to the target tissue in which ra-specific inflammation starts: a detailed mri study to improve identification of ra-specific features in the phase of clinically suspect arthralgia
title_auth	A search to the target tissue in which RA-specific inflammation starts: a detailed MRI study to improve identification of RA-specific features in the phase of clinically suspect arthralgia
abstract	Objective Based on a unique cohort of clinically suspect arthralgia (CSA) patients, we analysed which combinations of MRI features at onset were predictive for rheumatoid arthritis (RA) development. This was done to increase our comprehension of locations of RA onset and improve the predictive accuracy of MRI in CSA. Methods In the discovery cohort, 225 CSA patients were followed on clinical arthritis development. Contrast-enhanced 1.5 T MRIs were made of unilateral metacarpophalangeal (MCP) (2–5), wrist, and metatarsophalangeal (1–5) joints at baseline and scored for synovitis, tenosynovitis, and bone marrow edema. Severity, number, and combinations of locations (joint/tendon/bone) with subclinical inflammation were determined, with symptom-free controls of similar age category as reference. Cox regression was used for predictor selection. Predictive values were determined at 1 year follow-up. Results were validated in 209 CSA patients. Results In both cohorts, 15% developed arthritis < 1 year. The multivariable Cox model selected presence of MCP-extensor peritendinitis (HR 4.38 (2.07–9.25)) and the number of locations with subclinical inflammation (1–2 locations HR 2.54 (1.11–5.82); ≥ 3 locations HR 3.75 (1.49–9.48)) as predictors. Severity and combinations of inflammatory lesions were not selected. Based on these variables, five risk categories were defined: no subclinical inflammation, 1–2 locations, or ≥ 3 locations, with or without MCP-extensor peritendinitis. Positive predictive values (PPVs) ranged 5% (lowest category; NPV 95%) to 67% (highest category). Similar findings were obtained in the validation cohort; PPVs ranged 4% (lowest category; NPV 96%) to 63% (highest category). Conclusion Tenosynovitis, particularly MCP-extensor peritendinitis, is among the first tissues affected by RA. Incorporating this feature and number of locations with subclinical inflammation improved prediction making with PPVs up to 63–67%. © The Author(s). 2019
abstractGer	Objective Based on a unique cohort of clinically suspect arthralgia (CSA) patients, we analysed which combinations of MRI features at onset were predictive for rheumatoid arthritis (RA) development. This was done to increase our comprehension of locations of RA onset and improve the predictive accuracy of MRI in CSA. Methods In the discovery cohort, 225 CSA patients were followed on clinical arthritis development. Contrast-enhanced 1.5 T MRIs were made of unilateral metacarpophalangeal (MCP) (2–5), wrist, and metatarsophalangeal (1–5) joints at baseline and scored for synovitis, tenosynovitis, and bone marrow edema. Severity, number, and combinations of locations (joint/tendon/bone) with subclinical inflammation were determined, with symptom-free controls of similar age category as reference. Cox regression was used for predictor selection. Predictive values were determined at 1 year follow-up. Results were validated in 209 CSA patients. Results In both cohorts, 15% developed arthritis < 1 year. The multivariable Cox model selected presence of MCP-extensor peritendinitis (HR 4.38 (2.07–9.25)) and the number of locations with subclinical inflammation (1–2 locations HR 2.54 (1.11–5.82); ≥ 3 locations HR 3.75 (1.49–9.48)) as predictors. Severity and combinations of inflammatory lesions were not selected. Based on these variables, five risk categories were defined: no subclinical inflammation, 1–2 locations, or ≥ 3 locations, with or without MCP-extensor peritendinitis. Positive predictive values (PPVs) ranged 5% (lowest category; NPV 95%) to 67% (highest category). Similar findings were obtained in the validation cohort; PPVs ranged 4% (lowest category; NPV 96%) to 63% (highest category). Conclusion Tenosynovitis, particularly MCP-extensor peritendinitis, is among the first tissues affected by RA. Incorporating this feature and number of locations with subclinical inflammation improved prediction making with PPVs up to 63–67%. © The Author(s). 2019
abstract_unstemmed	Objective Based on a unique cohort of clinically suspect arthralgia (CSA) patients, we analysed which combinations of MRI features at onset were predictive for rheumatoid arthritis (RA) development. This was done to increase our comprehension of locations of RA onset and improve the predictive accuracy of MRI in CSA. Methods In the discovery cohort, 225 CSA patients were followed on clinical arthritis development. Contrast-enhanced 1.5 T MRIs were made of unilateral metacarpophalangeal (MCP) (2–5), wrist, and metatarsophalangeal (1–5) joints at baseline and scored for synovitis, tenosynovitis, and bone marrow edema. Severity, number, and combinations of locations (joint/tendon/bone) with subclinical inflammation were determined, with symptom-free controls of similar age category as reference. Cox regression was used for predictor selection. Predictive values were determined at 1 year follow-up. Results were validated in 209 CSA patients. Results In both cohorts, 15% developed arthritis < 1 year. The multivariable Cox model selected presence of MCP-extensor peritendinitis (HR 4.38 (2.07–9.25)) and the number of locations with subclinical inflammation (1–2 locations HR 2.54 (1.11–5.82); ≥ 3 locations HR 3.75 (1.49–9.48)) as predictors. Severity and combinations of inflammatory lesions were not selected. Based on these variables, five risk categories were defined: no subclinical inflammation, 1–2 locations, or ≥ 3 locations, with or without MCP-extensor peritendinitis. Positive predictive values (PPVs) ranged 5% (lowest category; NPV 95%) to 67% (highest category). Similar findings were obtained in the validation cohort; PPVs ranged 4% (lowest category; NPV 96%) to 63% (highest category). Conclusion Tenosynovitis, particularly MCP-extensor peritendinitis, is among the first tissues affected by RA. Incorporating this feature and number of locations with subclinical inflammation improved prediction making with PPVs up to 63–67%. © The Author(s). 2019
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title_short	A search to the target tissue in which RA-specific inflammation starts: a detailed MRI study to improve identification of RA-specific features in the phase of clinically suspect arthralgia
url	https://dx.doi.org/10.1186/s13075-019-2002-z
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author2	Wouters, Fenne Boeters, Debbie M. Boer, Aleid C. Dakkak, Yousra J. Niemantsverdriet, Ellis van der Helm-van Mil, Annette H. M.
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