Performance and calibration of the algorithm ASSIGN in predicting cardiovascular disease in Italian patients with psoriatic arthritis
- 44 Downloads
The increased cardiovascular (CV) risk is one of the major challenges in the management of patients with psoriatic arthritis (PsA). Recently, EULAR suggested to adapt the already available CV risk algorithms with a 1.5 multiplication factor in all the patients with rheumatoid arthritis (RA), but it is still uncertain if this adaptation could also be applied to patients with PsA. This study aims to evaluate the performance and calibration of the CV risk algorithm ASSIGN and its adaptations for RA (ASSIGN-RA) and according to EULAR recommendations in a cohort of patients with PsA (ASSIGN*1.5). Prospectively, collected data from two Italian cohorts has been analyzed. The discriminatory ability for CV risk prediction was assessed using the areas under the ROC curves. Calibration between predicted and observed events was assessed by Hosmer-Lemeshow (HL) test and calibration plots. For each algorithm, sensitivity and specificity were calculated for low- to high-risk cut-off (20%). One hundred fifty-five patients were enrolled with an observation of 1550 patient/years. Area under the ROC were 0.8179 (95% CI 0.72014 to 0.91558) for ASSIGN, 0.8160 (95% CI 0.71661 to 0.91529) for ASSIGN-RA, and 0.8179 (95% CI 0.72014 to 0.91558) for ASSIGN*1.5. HL tests did not demonstrate poor model fit for none of the algorithms. Discriminative ability and calibration were not improved by adaptation of the algorithms according to EULAR recommendations. Up to 20% of CV events occurred in patients at “low risk”. No difference in performance has been observed between ASSIGN, Progetto CUORE, and QRISK2. ASSIGN could represent a useful tool in predicting CV risk in patients with PsA. Adaptation for RA or according to EULAR recommendations did not show any further improvement in performance and calibration.
KeywordsASSIGN Cardiovascular disease Cardiovascular risk Psoriatic arthritis
Compliance with ethical standards
Conflict of interest
The authors declare they have no conflicts of interest.
- 1.Agca R, Heslinga SC, Rollefstad S, Heslinga M, McInnes IB, Peters MJ, Kvien TK, Dougados M, Radner H, Atzeni F, Primdahl J, Sodergren A, Wallberg Jonsson S, van Rompay J, Zabalan C, Pedersen TR, Jacobsson L, de Vlam K, Gonzalez-Gay MA, Semb AG, Kitas GD, Smulders YM, Szekanecz Z, Sattar N, Symmons DP, Nurmohamed MT (2017) EULAR recommendations for cardiovascular disease risk management in patients with rheumatoid arthritis and other forms of inflammatory joint disorders: 2015/2016 update. Ann Rheum Dis 76(1):17–28. https://doi.org/10.1136/annrheumdis-2016-209775 CrossRefGoogle Scholar
- 3.Ogdie A, Yu Y, Haynes K, Love TJ, Maliha S, Jiang Y, Troxel AB, Hennessy S, Kimmel SE, Margolis DJ, Choi H, Mehta NN, Gelfand JM (2015) Risk of major cardiovascular events in patients with psoriatic arthritis, psoriasis and rheumatoid arthritis: a population-based cohort study. Ann Rheum Dis 74(2):326–332. https://doi.org/10.1136/annrheumdis-2014-205675 CrossRefGoogle Scholar
- 7.Caso F, Del Puente A, Oliviero F, Peluso R, Girolimetto N, Bottiglieri P, Foglia F, Benigno C, Tasso M, Punzi L, Scarpa R, Costa L (2018) Metabolic syndrome in psoriatic arthritis: the interplay with cutaneous involvement. Evidences from literature and a recent cross-sectional study. Clin Rheumatol 37(3):579–586. https://doi.org/10.1007/s10067-017-3975-0 CrossRefGoogle Scholar
- 9.Ibanez-Bosch R, Restrepo-Velez J, Medina-Malone M, Garrido-Courel L, Paniagua-Zudaire I, Loza-Cortina E (2017) High prevalence of subclinical atherosclerosis in psoriatic arthritis patients: a study based on carotid ultrasound. Rheumatol Int 37(1):107–112. https://doi.org/10.1007/s00296-016-3617-x CrossRefGoogle Scholar
- 11.Abbas A, Gregersen I, Holm S, Daissormont I, Bjerkeli V, Krohg-Sorensen K, Skagen KR, Dahl TB, Russell D, Almas T, Bundgaard D, Alteheld LH, Rashidi A, Dahl CP, Michelsen AE, Biessen EA, Aukrust P, Halvorsen B, Skjelland M (2015) Interleukin 23 levels are increased in carotid atherosclerosis: possible role for the interleukin 23/interleukin 17 axis. Stroke 46(3):793–799. https://doi.org/10.1161/strokeaha.114.006516 CrossRefGoogle Scholar
- 12.Navarini L, Margiotta DPE, Caso F, Currado D, Tasso M, Angeletti S, Ciccozzi M, Scarpa R, Afeltra A, Costa L (2018) Performances of five risk algorithms in predicting cardiovascular events in patients with psoriatic arthritis: an Italian bicentric study. PLoS One 13(10):e0205506. https://doi.org/10.1371/journal.pone.0205506 CrossRefGoogle Scholar
- 13.Arts EE, Popa C, Den Broeder AA, Semb AG, Toms T, Kitas GD, van Riel PL, Fransen J (2015) Performance of four current risk algorithms in predicting cardiovascular events in patients with early rheumatoid arthritis. Ann Rheum Dis 74(4):668–674. https://doi.org/10.1136/annrheumdis-2013-204024 CrossRefGoogle Scholar
- 15.Hippisley-Cox J, Coupland C, Vinogradova Y, Robson J, Minhas R, Sheikh A, Brindle P (2008) Predicting cardiovascular risk in England and Wales: prospective derivation and validation of QRISK2. BMJ (Clinical research ed) 336(7659):1475–1482. https://doi.org/10.1136/bmj.39609.449676.25 CrossRefGoogle Scholar