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Artigo em Inglês | MEDLINE | ID: mdl-32433832


OBJECTIVE: The Systemic Lupus International Collaborating Clinics (SLICC) 2012 SLE classification criteria and the revised American College of Rheumatology (ACR) 1997 criteria are list-based, counting each SLE manifestation equally. We derived a classification rule based on giving variable weights to the SLICC criteria, and compared its performance to the revised ACR 1997, unweighted SLICC 2012 and the newly reported European League Against Rheumatism (EULAR)/ACR 2019 criteria. METHODS: The physician-rated patient scenarios used to develop the SLICC 2012 classification criteria were re-employed to devise a new weighted classification rule using multiple linear regression. The performance of the rule was evaluated on an independent set of expert-diagnosed patient scenarios and compared to the performance of the previously reported classification rules. RESULTS: Weighted SLICC criteria and the EULAR/ACR 2019 criteria had less sensitivity but better specificity compared to the list-based revised ACR 1997 and SLICC 2012 classification criteria. There were no statistically significant differences between any pair of rules with respect to overall agreement with the physician diagnosis. CONCLUSION: The two new weighted classification rules did not perform better than the existing list-based rules in terms of overall agreement on a dataset originally generated to assess the SLICC criteria. Given the added complexity of summing weights, researchers may prefer the unweighted SLICC criteria. However, the performance of a classification rule will always depend on the populations from which the cases and non-cases are derived, and whether the goal is to prioritize sensitivity or specificity.

Lupus Sci Med ; 6(1): e000348, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31649825


Objective: A common problem in clinical trials is missing data due to participant dropout and loss to follow-up, an issue which continues to receive considerable attention in the clinical research community. Our objective was to examine and compare current and alternative methods for handling missing data in SLE trials with a particular focus on multiple imputation, a flexible technique that has been applied in different disease settings but not to address missing data in the primary outcome of an SLE trial. Methods: Data on 279 patients with SLE randomised to standard of care (SoC) and also receiving mycophenolate mofetil (MMF), azathioprine or methotrexate were obtained from the Lupus Foundation of America-Collective Data Analysis Initiative Database. Complete case analysis (CC), last observation carried forward (LOCF), non-responder imputation (NRI) and multiple imputation (MI) were applied to handle missing data in an analysis to assess differences in SLE Responder Index-5 (SRI-5) response rates at 52 weeks between patients on SoC treated with MMF versus other immunosuppressants (non-MMF). Results: The rates of missing data were 32% in the MMF and 23% in the non-MMF groups. As expected, the NRI missing data approach yielded the lowest estimated response rates. The smallest and least significant estimates of differences between groups were observed with LOCF, and precision was lowest with the CC method. Estimated between-group differences were magnified with the MI approach, and imputing SRI-5 directly versus deriving SRI-5 after separately imputing its individual components yielded similar results. Conclusion: The potential advantages of applying MI to address missing data in an SLE trial include reduced bias when estimating treatment effects, and measures of precision that properly reflect uncertainty in the imputations. However, results can vary depending on the imputation model used, and the underlying assumptions should be plausible. Sensitivity analysis should be conducted to demonstrate robustness of results, especially when missing data proportions are high.

J Rheumatol ; 46(5): 492-500, 2019 05.
Artigo em Inglês | MEDLINE | ID: mdl-30647177


OBJECTIVE: In cross-sectional studies, elevated osteopontin (OPN) levels have been proposed to reflect, and/or precede, progressive organ damage and disease severity in systemic lupus erythematosus (SLE). We aimed, in a cohort of patients with recent-onset SLE, to determine whether raised serum OPN levels precede damage and/or are associated with disease activity or certain disease phenotypes. METHODS: We included 344 patients from the Systemic Lupus International Collaborating Clinics (SLICC) Inception Cohort who had 5 years of followup data available. All patients fulfilled the 1997 American College of Rheumatology (ACR) criteria. Baseline sera from patients and from age- and sex-matched population-based controls were analyzed for OPN using ELISA. Disease activity and damage were assessed at each annual followup visit using the SLE Disease Activity Index 2000 (SLEDAI-2K) and the SLICC/ACR damage index (SDI), respectively. RESULTS: Compared to controls, baseline OPN was raised 4-fold in SLE cases (p < 0.0001). After relevant adjustments in a binary logistic regression model, OPN levels failed to significantly predict global damage accrual defined as SDI ≥ 1 at 5 years. However, baseline OPN correlated with SLEDAI-2K at enrollment into the cohort (r = 0.27, p < 0.0001), and patients with high disease activity (SLEDAI-2K ≥ 5) had raised serum OPN (p < 0.0001). In addition, higher OPN levels were found in patients with persistent disease activity (p = 0.0006), in cases with renal involvement (p < 0.0001) and impaired estimated glomerular filtration rate (p = 0.01). CONCLUSION: The performance of OPN to predict development of organ damage was not impressive. However, OPN associated significantly with lupus nephritis and with raised disease activity at enrollment, as well as over time.

Ann Rheum Dis ; 78(7): 1010-1012, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-30573656
Lupus Sci Med ; 5(1): e000258, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29657738


Formidable impediments stand in the way of treatment development for lupus. These include the unwieldy size of current trials, international competition for scarce patients, complex outcome measures and a poor understanding of these outcomes in the world at large. The heterogeneity of the disease itself coupled to superimposition of variegated background polypharmacy has created enough immunological noise to virtually ensure the failure of lupus treatment trials, leaving an understandable suspicion that at least some of the results in testing failed drugs over the years may not have been negative, but merely uninterpretable. The authors have consulted with many clinical trial investigators, biopharmaceutical developers and stakeholders from government and voluntary sectors. This paper examines the available evidence that supports workable trial designs and proposes approaches to improve the odds of completing interpretable treatment development programs for lupus.