Can the adjusted mean SLEDAI-2K predict organ damage and coronary artery disease? (original) (raw)
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SLEDAI-2K Responder Index 50 captures 50% improvement in disease activity over 10 years
Lupus, 2012
Objectives: To determine the frequency and the time to complete recovery identified by Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) and the time to partial recovery identified by the SLEDAI-2K Responder Index 50 (SRI-50) in three laboratory systems over 10 years. Methods: This is a retrospective analysis of the data available from the Toronto Lupus Clinic over the last 10 years. Patients with SLEDAI-2K renal, immunological and hematologic active descriptors were identified. The percentage of descriptors with partial and complete recovery was studied at one year and over the study period. Descriptive analysis and the Kaplan-Meier estimator were applied to study the time to partial and complete recovery. Results: Of the 795 patients, 94% had an active system at some point during the study period. Partial recovery was shown in 66% of patients by SRI-50 for at least one descriptor over the study period. None of these partial findings identified would have been captured using SLEDAI-2K alone. The time to partial recovery identified by SRI-50 was shorter than the time to complete recovery identified by SLEDAI-2K. Conclusion: The SRI-50 is a valid responder index derived form SLEDAI-2K and is very helpful in identifying clinically important improvement in active laboratory descriptors in an efficient time. Lupus (2012) 21, 1305-1311.
Rheumatology, 2011
Objectives. To examine SLEDAI-2000 cutoff scores for definition of active SLE and to determine the sensitivity to change of SLEDAI-2000 for the assessment of SLE disease activity and minimal clinically meaningful changes in score. Methods. Data from two multi-centre studies were used in the analysis: in a cross-sectional and a longitudinal fashion. At every assessment, data were collected on SLEDAI-2000 and treatment. The cross-sectional analysis with receiver operating characteristic (ROC) curves was used to examine the appropriate SLEDAI-2000 score to define active disease and increase in therapy was the reference standard. In the longitudinal analysis, sensitivity to change of SLEDAI-2000 was assessed with multinomial logistic regression. ROC curves analysis was used to examine possible cut-points in score changes associated with change in therapy, and mean changes were estimated. Results. In the cross-sectional analysis, the most appropriate cutoff scores for active disease were 3 or 4. In the longitudinal analysis, the best model for predicting treatment increase was with the change in SLEDAI-2000 score and the score from the previous visit as continuous variables. The use of cut-points was less predictive of treatment change than the use of continuous score. The mean difference in the change in SLEDAI-2000 scores, adjusted for prior score, between patients with treatment increase and those without was 2.64 (95% CI 2.16, 3.14). Conclusions. An appropriate SLEDAI-2000 score to define active disease is 3 or 4. SLEDAI-2000 index is sensitive to change. The use of SLEDAI-2000 as a continuous outcome is recommended for comparative purposes.
Derivation of the sledai. A disease activity index for lupus patients
Arthritis and Rheumatism, 1992
Objective. To standardize outcome measures in systemic lupus erythematosus (SLE). Three indices were identified which could adequately describe outcome (disease activity, damage from disease, and health status); we describe here the development of the Disease Activity Index.Methods. Twenty-four variables were identified as important factors in a disease activity index. These were used to generate 574 patient profiles, which were rated on a disease activity scale of 0–10 by 14 rheumatologists. A second rating of 10 of the profiles yielded scores that were not significantly different from the first, indicating that experienced clinicians can reliably make global estimates of disease activity. Multiple regression models were used to estimate the relative importance of the 24 clinical variables in the physicians' global rating of disease activity. These were estimated on a ‘training set’ of 75% of physicians' ratings, and then validated on a ‘testing set,’ consisting of the remaining 25% of physicians' ratings.Results. The explanatory power of the models in the training set was high (R2 = 0.93). The models' regression coefficients for the organ systems were simplified for easier use in clinical practice. This generated a ‘weighted’ index of 9 organ systems for disease activity in SLE, the SLEDAI, as follows: 8 for central nervous system and vascular, 4 for renal and musculoskeletal, 2 for serosal, dermal, immunologic, and 1 for constitutional and hematologic. The maximum theoretical score is 105, but in practice, few patients have scores greater than 45. The SLEDAI predicted well the physicians' ratings in the testing set (Pearson's correlation coefficients = 0.64–0.79).Conclusion. The SLEDAI is a validated model of experienced clinicians' global assessments of disease activity in lupus. It represents the consensus of a group of experts in the field of lupus research.
Lupus, 2019
The objective of this paper is to evaluate the performance of the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI-2K) in detecting clinically meaningful changes in SLE disease activity. Methods: A longitudinal cohort study was conducted of 334 SLE patients during a 36-month follow-up. At each outpatient visit, disease activity was scored using the Physician Global Assessment (PGA) and SLEDAI-2K. Correlations between PGA and SLEDAI-2K were assessed. A clinically meaningful change in SLE disease activity was defined as a ÁPGA ! 0.3 points from baseline. Performance of SLEDAI-2K in detecting a clinically meaningful worsening or improvement was tested using receiver operating characteristic (ROC) analysis. Results: Adjusted mean PGA and SLEDAI-2K scores presented a high correlation (rho ¼ 0.824, p < 0.0005). In ROC analysis, a SLEDAI-2K variation presented an area under the curve (AUC) of 0.697 (95% confidence interval (CI) (0.628-0.766), p < 0.0005) to detect a clinically meaningful improvement, with a sensitivity of 28.8% for a SLEDAI-2K ! 4 reduction. The AUC to detect a clinically meaningful worsening was 0.877 (95% CI (0.822-0.932), p < 0.0005), with a sensitivity of 35.3%. Conclusions: SLEDAI-2K has a limited ability to detect clinically meaningful changes in SLE disease activity, failing to identify almost two-thirds of cases judged as having a clinically meaningful improvement or worsening. There is a need for more sensitive SLE disease activity measures in clinical practice and research. Lupus (2019) 0, 1-6.
Arthritis & Rheumatism, 2007
Results. In 552 patients, the SF-6D was negatively associated with damage accrual and mortality in the univariable analyses; the association with damage was confirmed in the multivariable analyses ( 2 ؍ 9.020, P ؍ 0.002) but the association with mortality was not confirmed (hazard ratio 0.495, 95% confidence interval 0.041-6.038). When the PCS and MCS were evaluated, the PCS, but not the MCS, was found to be associated with damage but not with mortality. Conclusion. The SF-6D (and the PCS) as measured early in the disease course were found to independently predict damage accrual at the last visit, but not mortality. Although the SF-6D was originally conceived as a utility measure, it may be used to accurately assess overall health status in patients with SLE. KEY WORDS. SF-6D; Health-related quality of life; Short Form 36; Damage; Mortality; Systemic lupus erythematosus.
BILAG-2004 index captures systemic lupus erythematosus disease activity better than SLEDAI-2000
Annals of the Rheumatic Diseases, 2008
Objective: To assess the reliability of Systemic Lupus Erythematosus Disease Activity Index (SLEDAI)-2000 index in routine practice and its ability to capture disease activity as compared with the British Isles Lupus Assessment Group (BILAG)-2004 index. Methods: Patients with systemic lupus erythematosus from 11 centres were assessed separately by two raters in routine practice. Disease activity was assessed using the BILAG-2004 and SLEDAI-2000 indices. The level of agreement for items was used to assess the reliability of SLEDAI-2000. The ability to detect disease activity was assessed by determining the number of patients with a high activity on BILAG-2004 (overall score A or B) but low SLEDAI-2000 score (,6) and number of patients with low activity on BILAG-2004 (overall score C, D or E) but high SLEDAI-2000 score (>6). Treatment of these patients was analysed, and the increase in treatment was used as the gold standard for active disease. Results: 93 patients (90.3% women, 69.9% Caucasian) were studied: mean age was 43.8 years, mean disease duration 10 years. There were 43 patients (46.2%) with a difference in SLEDAI-2000 score between the two raters and this difference was >4 in 19 patients (20.4%). Agreement for each of the items in SLEDAI-2000 was between 81.7 and 100%. 35 patients (37.6%) had high activity on BILAG-2004 but a low SLEDAI-2000 score, of which 48.6% had treatment increased. There were only five patients (5.4%) with low activity on BILAG-2004 but a high SLEDAI-2000 score. Conclusions: SLEDAI-2000 is a reliable index to assess systemic lupus erythematosus disease activity but it is less able than the BILAG-2004 index to detect active disease requiring increased treatment.
Clinical SLEDAI-2K zero may be a pragmatic outcome measure in SLE studies
Expert Opinion on Biological Therapy, 2018
Objectives: Development of therapies for systemic lupus erythematosus (SLE) has in part been limited by the lack of suitable outcome measures in clinical trials. In the present posthoc analysis of two clinical trials of belimumab, we investigated two potential outcomes, the Lupus Low Disease Activity State (LLDAS) and clinical SLE disease activity index 2000 (cSLEDAI-2K) zero, in relation to SLE responder index 4 (SRI-4). A c c e p t e d M a n u s c r i p t Methods: A total of 1684 SLE patients from the BLISS-52 (n=865) and BLISS-76 (n=819) trials were surveyed. Physician's Global Assessment (PGA) scores <0.5 (3-point scale) were used for comparisons. We used the chi-square test for comparisons and the phi coefficient for correlations. Results: At week 52, LLDAS was achieved by 8.6% of patients, cSLEDAI-2K=0 by 34.5% and SRI-4 by 45.1%. cSLEDAI-2K=0 showed the strongest correlation with PGA <0.5 (r φ =0.36, P<0.001). cSLEDAI-2K=0 unveiled the superiority of belimumab 10 mg/kg over placebo (P=0.003) with a magnitude which was comparable to that of SRI-4 (P<0.001). LLDAS displayed a more moderate separation (P=0.033). Conclusions: LLDAS was a stringent measure. cSLEDAI-2K=0 showed the strongest correlation with the clinician-based evaluation. Being based on the SLEDAI-2K only, cSLEDAI-2K=0 may be considered a more pragmatic outcome measure in SLE studies compared with composite tools.
Arthritis & rheumatology, 2019
Objective:To evaluate the properties of a frailty index (FI), constructed using data from the Systemic Lupus International Collaborating Clinics (SLICC) inception cohort, as a novel health measure in SLE.Methods:For this secondary analysis, the baseline visit was defined as the first study visit at which both organ damage (SLICC/ACR Damage Index [SDI]) and health-related quality of life (Short-Form 36 [SF-36]) were assessed. The SLICC-FI was constructed using baseline data. The SLICC-FI comprises 48 health deficits, including items related to organ damage, disease activity, comorbidities, and functional status. Content, construct, and criterion validity of the SLICC-FI were assessed. Multivariable Cox regression was used to estimate the association between baseline SLICC-FI values and mortality risk, adjusting for demographic and clinical factors.Results:The 1683 SLE patients in the baseline dataset were 89% female with mean (SD) age 35.7 (13.4) years and mean (SD) disease duration 18.8 (15.7) months. At baseline, the mean (SD) SLICC-FI score was 0.17 (0.08) with a range from 0 to 0.51. Baseline SLICC-FI values exhibited the expected measurement properties and were weakly correlated with baseline SDI scores (r=0.262; p<0.0001). Higher baseline SLICC-FI values (per 0.05 increment) were associated with increased mortality risk (Hazard Ratio 1.59; 95%CI 1.35–1.87), after adjusting for age, sex, steroid use, ethnicity/region, and baseline SDI scores.Conclusion:The SLICC-FI demonstrates internal validity as a health measure in SLE and predicts future mortality risk. The SLICC-FI is potentially valuable for quantifying vulnerability among patients with SLE, and adds to existing prognostic scores.
Novel cardiovascular risk prediction models in patients with systemic lupus erythematosus
Lupus, 2011
Women with systemic lupus erythematosus (SLE) have increased risk for coronary heart disease (CHD) which is underestimated by the Framingham risk score (FRS). We hypothesized that new risk scores that include inflammation or vascular age in the risk calculation would better identify women with SLE at risk for CHD, particularly in those with subclinical coronary atherosclerosis. We calculated the FRS and Reynolds risk score (RRS) in 121 women with SLE and 65 agematched female controls; coronary age-modified risk scores (camFRS, camRRS) were calculated using coronary age derived from the coronary artery calcium (CAC) score. Risk scores were compared in SLE and controls, and in SLE patients with and without CAC. Although CAC was present in 21 SLE patients (17%) and 4 controls (6%) (P=0.033); the FRS, camFRS, RRS, and camRRS, did not differ significantly among SLE and controls (P>0.05), but were all significantly higher in SLE patients with CAC compared to those without (P< 0.001 for all). The cam-FRS (8%, P=0.016) but not cam-RRS (5%, P=0.221) assigned significantly more SLE patients to a category of ≥10% risk than conventional FRS (1%) and RRS (2%). The RRS was of limited use but coronary age may improve CHD risk prediction in SLE.