OBJECTIVE: There is a need to identify clinical characteristics and/or biomarkers that can predict treatment outcome in lupus nephritis. To this end, we utilized data from the Aspreva Lupus Management Study to identify possible baseline and early predictors of renal response to mycophenolate mofetil (MMF) or intravenous (IV) cyclophosphamide (CYC). METHODS:Patients with class III-V lupus nephritis were randomized to MMF or IV CYC. We assessed predictors of renal response, including baseline demographic, clinical, laboratory, and histologic characteristics, as well as early clinical and laboratory data, obtained within the first 2 months of therapy. Odds ratios (ORs) and 95% confidence intervals for renal response were calculated for each putative predictor. RESULTS: Normalization of C3, C4, or both by week 8 was strongly predictive of renal response at week 24 (ORs 2.5, 2.6, and 2.9, respectively; P < 0.05). Reduction in proteinuria by ≥25% by week 8 was predictive of renal response at week 24 (OR 3.2, P < 0.05). Reduction in anti-double-stranded DNA (anti-dsDNA) by week 8 was not predictive of renal response. Only 3 baseline characteristics (C4 level, time since diagnosis of lupus nephritis, and estimated glomerular filtration rate [GFR]) were predictive of renal response; the remaining characteristics (age, age at lupus nephritis onset, time since diagnosis of systemic lupus erythematosus, sex, histopathologic class, anti-dsDNA antibody level, C3 level, level of proteinuria, and use of angiotensin-converting enzyme inhibitors, statins, or hydroxychloroquine) were not. CONCLUSION: This study demonstrates that baseline C4 level, time since diagnosis of lupus nephritis, baseline estimated GFR, early normalization of complement, and reduction in proteinuria independently predict renal response to therapy at 6 months.
RCT Entities:
OBJECTIVE: There is a need to identify clinical characteristics and/or biomarkers that can predict treatment outcome in lupus nephritis. To this end, we utilized data from the Aspreva Lupus Management Study to identify possible baseline and early predictors of renal response to mycophenolate mofetil (MMF) or intravenous (IV) cyclophosphamide (CYC). METHODS:Patients with class III-V lupus nephritis were randomized to MMF or IV CYC. We assessed predictors of renal response, including baseline demographic, clinical, laboratory, and histologic characteristics, as well as early clinical and laboratory data, obtained within the first 2 months of therapy. Odds ratios (ORs) and 95% confidence intervals for renal response were calculated for each putative predictor. RESULTS: Normalization of C3, C4, or both by week 8 was strongly predictive of renal response at week 24 (ORs 2.5, 2.6, and 2.9, respectively; P < 0.05). Reduction in proteinuria by ≥25% by week 8 was predictive of renal response at week 24 (OR 3.2, P < 0.05). Reduction in anti-double-stranded DNA (anti-dsDNA) by week 8 was not predictive of renal response. Only 3 baseline characteristics (C4 level, time since diagnosis of lupus nephritis, and estimated glomerular filtration rate [GFR]) were predictive of renal response; the remaining characteristics (age, age at lupus nephritis onset, time since diagnosis of systemic lupus erythematosus, sex, histopathologic class, anti-dsDNA antibody level, C3 level, level of proteinuria, and use of angiotensin-converting enzyme inhibitors, statins, or hydroxychloroquine) were not. CONCLUSION: This study demonstrates that baseline C4 level, time since diagnosis of lupus nephritis, baseline estimated GFR, early normalization of complement, and reduction in proteinuria independently predict renal response to therapy at 6 months.
Authors: Bevra H Hahn; Maureen A McMahon; Alan Wilkinson; W Dean Wallace; David I Daikh; John D Fitzgerald; George A Karpouzas; Joan T Merrill; Daniel J Wallace; Jinoos Yazdany; Rosalind Ramsey-Goldman; Karandeep Singh; Mazdak Khalighi; Soo-In Choi; Maneesh Gogia; Suzanne Kafaja; Mohammad Kamgar; Christine Lau; William J Martin; Sefali Parikh; Justin Peng; Anjay Rastogi; Weiling Chen; Jennifer M Grossman Journal: Arthritis Care Res (Hoboken) Date: 2012-06 Impact factor: 4.794
Authors: Peter M Izmirly; Marianna Shvartsbeyn; Shane Meehan; Andrew Franks; Alan Braun; Ellen Ginzler; Sherry X Xu; Herman Yee; Tania L Rivera; Tania Rivera; Charles Esmon; Laura Barisoni; Joan T Merrill; Jill P Buyon; Robert M Clancy Journal: J Rheumatol Date: 2012-02-01 Impact factor: 4.666
Authors: C Reátegui-Sokolova; Manuel F Ugarte-Gil; Rocío V Gamboa-Cárdenas; Francisco Zevallos; Jorge M Cucho-Venegas; José L Alfaro-Lozano; Mariela Medina; Zoila Rodriguez-Bellido; Cesar A Pastor-Asurza; Graciela S Alarcón; Risto A Perich-Campos Journal: Clin Rheumatol Date: 2017-01-18 Impact factor: 2.980
Authors: David J Tunnicliffe; Suetonia C Palmer; Lorna Henderson; Philip Masson; Jonathan C Craig; Allison Tong; Davinder Singh-Grewal; Robert S Flanc; Matthew A Roberts; Angela C Webster; Giovanni Fm Strippoli Journal: Cochrane Database Syst Rev Date: 2018-06-29