External validation of the accuracy of cardiovascular risk prediction tools in psoriatic disease: a UK Biobank study

被引:0
作者
Hughes, David M. [1 ]
Yiu, Zenas Z. N. [2 ,3 ]
Zhao, Sizheng Steven [4 ]
机构
[1] Univ Liverpool, Dept Hlth Data Sci, Liverpool, England
[2] Univ Manchester, Northern Care Alliance NHS Fdn Trust, Natl Inst Hlth, Ctr Dermatol Res,Manchester Acad Hlth Sci Ctr, Manchester, England
[3] Care Res Manchester Biomed Res Ctr, Manchester, England
[4] Univ Manchester, Manchester Acad Hlth Sci Ctr, Ctr Musculoskeletal Res, Fac Biol Med & Hlth,Div Musculoskeletal & Dermatol, Manchester, England
关键词
Cardiovascular risk prediction; Psoriasis; Psoriatic arthritis; Rheumatoid arthritis; UK Biobank; Validation; RHEUMATOID-ARTHRITIS; SCORE; ALGORITHMS; EVENTS;
D O I
10.1007/s10067-025-07325-y
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
IntroductionRisk prediction is important for preventing and managing cardiovascular disease (CVD). CVD risk prediction tools designed for the general population may be inaccurate in people with inflammatory diseases.ObjectivesTo investigate the performance of four cardiovascular risk prediction tools (QRISK3, Framingham Risk Score, Reynolds Risk Score and SCORE) in psoriatic arthritis (PsA) and psoriasis. We also compare performance in participants with no inflammatory conditions and in people with rheumatoid arthritis (RA).MethodsThis research utilised the UK Biobank Resource. We identified participants with PsA, psoriasis and RA and calculated their cardiovascular risk using each risk tool. We assessed model calibration by comparing observed and predicted outcomes. Discrimination of 10-year risk prediction was assessed using time-dependent area under ROC curve (AUC), sensitivity, specificity, positive and negative predictive values.ResultsWe included 769 individuals with PsA, 8062 with psoriasis and 4772 with RA when assessing the QRISK3 tool. Predictions for individuals with psoriasis were roughly as accurate as those with no inflammatory conditions with time-dependent AUC of 0.74 (95%CI, 0.72, 0.76) and of 0.74 (95%CI, 0.72, 0.77) respectively. In contrast, individuals with PsA obtained the least accurate predictions with an AUC of 0.70 (95%CI, 0.64, 0.76). Individuals with RA also obtained less accurate predictions with AUC of 0.72 (0.69,0.74). For the Framingham risk score, AUCs varied between 0.61 (95%CI, 0.55, 0.68) for participants with PsA and 0.71 (95%CI, 0.68, 0.74) for individuals with no inflammatory condition.ConclusionsIn general, CVD risk prediction accuracy was similar for individuals with psoriasis or no inflammatory condition, but lower for individuals with PsA or RA.
引用
收藏
页码:1151 / 1161
页数:11
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共 32 条
[11]   Challenges of developing a cardiovascular risk calculator for patients with rheumatoid arthritis [J].
Crowson, Cynthia S. ;
Rollefstad, Silvia ;
Kitas, George D. ;
van Riel, Piet L. C. M. ;
Gabriel, Sherine E. ;
Semb, Anne Grete .
PLOS ONE, 2017, 12 (03)
[12]   General cardiovascular risk profile for use in primary care - The Framingham Heart Study [J].
D'Agostino, Ralph B. ;
Vasan, Ramachandran S. ;
Pencina, Michael J. ;
Wolf, Philip A. ;
Cobain, Mark ;
Massaro, Joseph M. ;
Kannel, William B. .
CIRCULATION, 2008, 117 (06) :743-753
[13]   Joint AAD-NPF guidelines of care for the management and treatment of psoriasis with awareness and attention to comorbidities [J].
Elmets, Craig A. ;
Leonardi, Craig L. ;
Davis, Dawn M. R. ;
Gelfand, Joel M. ;
Lichten, Jason ;
Mehta, Nehal N. ;
Armstrong, April W. ;
Connor, Cody ;
Cordoro, Kelly M. ;
Elewski, Boni E. ;
Gordon, Kenneth B. ;
Gottlieb, Alice B. ;
Kaplan, Daniel H. ;
Kavanaugh, Arthur ;
Kivelevitch, Dario ;
Kiselica, Matthew ;
Korman, Neil J. ;
Kroshinsky, Daniela ;
Lebwohl, Mark ;
Lim, Henry W. ;
Paller, Amy S. ;
Parra, Sylvia L. ;
Pathy, Arun L. ;
Prater, Elizabeth Farley ;
Rupani, Reena ;
Siegel, Michael ;
Stoff, Benjamin ;
Strober, Bruce E. ;
Wong, Emily B. ;
Wu, Jashin J. ;
Hariharan, Vidhya ;
Menter, Alan .
JOURNAL OF THE AMERICAN ACADEMY OF DERMATOLOGY, 2019, 80 (04) :1073-1113
[14]   Comparison of Sociodemographic and Health-Related Characteristics of UK Biobank Participants With Those of the General Population [J].
Fry, Anna ;
Littlejohns, Thomas J. ;
Sudlow, Cathie ;
Doherty, Nicola ;
Adamska, Ligia ;
Sprosen, Tim ;
Collins, Rory ;
Allen, Naomi E. .
AMERICAN JOURNAL OF EPIDEMIOLOGY, 2017, 186 (09) :1026-1034
[15]   Estimating a time-dependentconcordance index for survival prediction models with covariate dependent censoring [J].
Gerds, Thomas A. ;
Kattan, Michael W. ;
Schumacher, Martin ;
Yu, Changhong .
STATISTICS IN MEDICINE, 2013, 32 (13) :2173-2184
[16]   Development and validation of QRISK3 risk prediction algorithms to estimate future risk of cardiovascular disease: prospective cohort study [J].
Hippisley-Cox, Julia ;
Coupland, Carol ;
Brindle, Peter .
BMJ-BRITISH MEDICAL JOURNAL, 2017, 357
[17]   The predictive accuracy of cardiovascular disease risk prediction tools in inflammatory arthritis and psoriasis: an observational validation study using the Clinical Practice Research Datalink [J].
Hughes, David ;
Coronado, Jose Ignacio Cuitun ;
Schofield, Pieta ;
Yiu, Zenas ;
Zhao, Sizheng Steven .
RHEUMATOLOGY, 2023, 63 (12) :3432-3441
[18]   Combined use of QRISK3 and SCORE2 increases identification of ankylosing spondylitis patients at high cardiovascular risk: Results from the CARMA Project cohort after 7.5 years of follow-up [J].
la Borda, Jessica Polo y ;
Castaneda, Santos ;
Sanchez-Alonso, Fernando ;
Plaza, Zulema ;
Garcia-Gomez, Carmen ;
Ferraz-Amaro, Ivan ;
Erausquin, Celia ;
Valls-Garcia, Ramon ;
Fabregas, Maria D. ;
Delgado-Frias, Esmeralda ;
Mas, Antonio J. ;
Gonzalez-Juanatey, Carlos ;
Llorca, Javier ;
Gonzalez-Gay, Miguel A. .
SEMINARS IN ARTHRITIS AND RHEUMATISM, 2024, 66
[19]   Cardiovascular morbidity and mortality in ankylosing spondylitis and psoriatic arthritis [J].
Liew, Jean W. ;
Ramiro, Sofia ;
Gensler, Lianne S. .
BEST PRACTICE & RESEARCH IN CLINICAL RHEUMATOLOGY, 2018, 32 (03) :369-389
[20]   Performance of the Expanded Cardiovascular Risk Prediction Score for Rheumatoid Arthritis in a geographically distant National Register-based cohort: an external validation [J].
Ljung, Lotta ;
Ueda, Peter ;
Liao, Katherine P. ;
Greenberg, Jeffrey D. ;
Etzel, Carol J. ;
Solomon, Daniel H. ;
Askling, Johan .
RMD OPEN, 2018, 4 (02)