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000292493 1001_ $$00009-0006-9688-3697$$aZuern, Kosima$$b0
000292493 245__ $$aLongitudinal assessment of established risk stratification models in patients with monoclonal gammopathy of undetermined significance.
000292493 260__ $$aLondon [u.a.]$$bNature Publishing Group$$c2024
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000292493 520__ $$aRisk of progression of monoclonal gammopathy of undetermined significance (MGUS) into multiple myeloma and related plasma cell disorders can be determined by three major risk stratification models, namely Mayo2005, Sweden2014, and NCI2019. This retrospective study of 427 patients with MGUS diagnosed according to the 2014 International Myeloma Working Group criteria aimed to describe and analyze the longitudinal applicability of these risk models. In all three models, the majority of patients remained at their baseline risk group, whereas small numbers of patients migrated to a different risk group. Proportions of patients among risk groups remained stable over time (e.g. Mayo2005 model, low-risk group, at baseline: 43%, after 1, 2, 3, 4, 5, and 8 years: 40%, 37%, 37%, 43%, 44%, and 43%). All three risk models reliably distinguished risk of progression at baseline, upon yearly reassessment (e.g. 1 year from diagnosis) and in time-dependent analyses. Upstaging to a high-risk category was associated with an increased risk of progression in all three models (Mayo2005: hazard ratio [HR] = 5.43, 95% confidence interval [95% CI] 1.21-24.39, p = 0.027; Sweden2014: HR = 13.02, 95% CI 5.25-32.28, p < 0.001; NCI2019: HR = 5.85, 95% CI 2.49-13.74, p < 0.001). Our study shows that MGUS risk stratification models can be applied longitudinally to repeatedly determine and improve individual risk of progression. Patient migration to higher risk categories during follow up should prompt more frequent monitoring in clinical routine.
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000292493 650_2 $$2MeSH$$aHumans
000292493 650_2 $$2MeSH$$aMonoclonal Gammopathy of Undetermined Significance: epidemiology
000292493 650_2 $$2MeSH$$aMonoclonal Gammopathy of Undetermined Significance: diagnosis
000292493 650_2 $$2MeSH$$aMale
000292493 650_2 $$2MeSH$$aFemale
000292493 650_2 $$2MeSH$$aAged
000292493 650_2 $$2MeSH$$aMiddle Aged
000292493 650_2 $$2MeSH$$aDisease Progression
000292493 650_2 $$2MeSH$$aRetrospective Studies
000292493 650_2 $$2MeSH$$aRisk Assessment
000292493 650_2 $$2MeSH$$aAged, 80 and over
000292493 650_2 $$2MeSH$$aLongitudinal Studies
000292493 650_2 $$2MeSH$$aAdult
000292493 650_2 $$2MeSH$$aMultiple Myeloma: epidemiology
000292493 650_2 $$2MeSH$$aMultiple Myeloma: diagnosis
000292493 650_2 $$2MeSH$$aRisk Factors
000292493 7001_ $$0P:(DE-He78)743a4a82daab55306a2c88b9f6bf8c2f$$aHielscher, Thomas$$b1$$udkfz
000292493 7001_ $$aWerly, Annika$$b2
000292493 7001_ $$aBreitkreutz, Iris$$b3
000292493 7001_ $$aSauer, Sandra$$b4
000292493 7001_ $$aRaab, Marc S$$b5
000292493 7001_ $$aMüller-Tidow, Carsten$$b6
000292493 7001_ $$aGoldschmidt, Hartmut$$b7
000292493 7001_ $$00000-0002-6226-1252$$aMai, Elias K$$b8
000292493 773__ $$0PERI:(DE-600)2600560-8$$a10.1038/s41408-024-01126-3$$gVol. 14, no. 1, p. 148$$n1$$p148$$tBlood cancer journal$$v14$$x2044-5385$$y2024
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