Use of risk chart algorithms for the identification of psoriatic arthritis patients at high risk for cardiovascular disease: findings derived from the project CARMA cohort after a 7.5-year follow-up period.

OBJECTIVE: To assess the predictive value of four cardiovascular (CV) risk algorithms for identifying high-risk psoriatic arthritis (PsA) patients. METHODS: Evaluation of patients with PsA enrolled in the Spanish prospective project CARdiovascular in RheuMAtology. Baseline data of 669 PsA patients with no history of CV events at the baseline visit, who were followed in rheumatology outpatient clinics at tertiary centres for 7.5 years, were retrospectively analysed to test the performance of the Systematic Coronary Risk Assessment (SCORE), the modified version (mSCORE) European Alliance of Rheumatology Associations (EULAR) 2015/2016, the SCORE2 algorithm (the updated and improved version of SCORE) and the QRESEARCH risk estimator version 3 (QRISK3). RESULTS: Over 4790 years of follow-up, there were 34 CV events, resulting in a linearised rate of 7.10 per 1000 person-years (95% CI 4.92 to 9.92). The four CV risk scales showed strong correlations and all showed significant associations with CV events (p<0.001). SCORE, mSCORE EULAR 2015/2016 and QRISK3 effectively differentiated between low and high CV risk patients, although the cumulative rate of CV events observed over 7.5 years was lower than expected based on the frequency predicted by these risk scales. Additionally, model improvement was observed when combining QRISK3 with any other scale, particularly the combination of QRISK3 and SCORE2, which yielded the lowest Akaike information criterion (411.15) and Bayesian information criterion (420.10), making it the best predictive model. CONCLUSIONS: Risk chart algorithms are very useful for discriminating PsA at low and high CV risk. An integrated model featuring QRISK3 and SCORE2 yielded the optimal synergy of QRISK3's discrimination ability and SCORE2's calibration accuracy.

Interobserver Reliability and Sensitivity to Change of a Composite Ocular Inflammatory Activity Index: UVEDAI©.

INTRODUCTION: This was a multicenter, prospective, longitudinal, observational study involving eight Spanish tertiary hospitals to determine the interobserver reliability of an uveitis disease activity index, (UVEDAI) and assess its sensitivity to change in patients with receiving pharmacologic treatment. METHODS: Patients aged ≥ 18 years diagnosed with active noninfectious uveitis were included. A complete baseline assessment was performed by two ophthalmologists who determined ocular inflammatory activity using the UVEDAI index independently of each other. The principal ophthalmologist made a new visit at 4 weeks to determine the change in inflammatory activity. The interobserver reliability analysis was performed by calculating the intraclass correlation coefficient (ICC), with the values of the variables and the UVEDAI obtained by both ophthalmologists in the more active eye at the baseline visit. Sensitivity to change in the UVEDAI index was assessed at 4 weeks from the start of pharmacologic treatment by determining the clinically relevant change, defined as a change in UVEDAI of ≥ 0.8 points over baseline. The mean change between both measures was compared using the repeated-measures t-test. RESULTS: A total of 111 patients were included. In the interobserver reliability analysis, the ICC for the UVEDAI value was 0.9, and, when compared with the mean UVEDAI values obtained by the ophthalmologists, no statistically significant differences were found (p value > 0.05). As for the sensitivity to change in UVEDAI, statistically significant differences (p value = 0.00) were found for the mean values of the index compared with baseline. In all cases, the index value decreased by > 1 point at the 4-week visit. CONCLUSIONS: The interobserver reliability of the UVEDAI was high in the total sample. Furthermore, the index was sensitive in determining the change in inflammatory activity after treatment. We believe that UVEDAI is a disease activity index that enables objective comparison of results in clinical practice and trials.

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.

OBJECTIVE: To establish the predictive value of the QRESEARCH risk estimator version 3 (QRISK3) algorithm in identifying Spanish patients with ankylosing spondylitis (AS) at high risk of cardiovascular (CV) events and CV mortality. We also sought to determine whether to combine QRISK3 with another CV risk algorithm: the traditional SCORE, the modified SCORE (mSCORE) EULAR 2015/2016 or the SCORE2 may increase the identification of AS patients with high-risk CV disease. METHODS: Information of 684 patients with AS from the Spanish prospective CARdiovascular in ReuMAtology (CARMA) project who at the time of the initial visit had no history of CV events and were followed in rheumatology outpatient clinics of tertiary centers for 7.5 years was reviewed. The risk chart algorithms were retrospectively tested using baseline data. RESULTS: After 4,907 years of follow-up, 33 AS patients had experienced CV events. Linearized rate=6.73 per 1000 person-years (95 % CI: 4.63, 9.44). The four CV risk scales were strongly correlated. QRISK3 correctly discriminated between people with lower and higher CV risk, although the percentage of accumulated events over 7.5 years was clearly lower than expected according to the risk established by QRISK3. Also, mSCORE EULAR 2015/2016 showed the same discrimination ability as SCORE, although the percentage of predicted events was clearly higher than the percentage of actual events. SCORE2 also had a strong discrimination capacity according to CV risk. Combining QRISK3 with any other scale improved the model. This was especially true for the combination of QRISK3 and SCORE2 which achieved the lowest AIC (406.70) and BIC (415.66), so this combination would be the best predictive model. CONCLUSIONS: In patients from the Spanish CARMA project, the four algorithms tested accurately discriminated those AS patients with higher CV risk and those with lower CV risk. Moreover, a model that includes QRISK3 and SCORE2 combined the best discrimination ability of QRISK3 with the best calibration of SCORE2.