Predictors of clinical outcomes in patients with neuropsychiatric systemic lupus erythematosus. (March 2016)
- Record Type:
- Journal Article
- Title:
- Predictors of clinical outcomes in patients with neuropsychiatric systemic lupus erythematosus. (March 2016)
- Main Title:
- Predictors of clinical outcomes in patients with neuropsychiatric systemic lupus erythematosus
- Authors:
- Ichinose, Kunihiro
Arima, Kazuhiko
Umeda, Masataka
Fukui, Shoichi
Nishino, Ayako
Nakashima, Yoshikazu
Suzuki, Takahisa
Horai, Yoshiro
Koga, Tomohiro
Kawashiri, Shin-ya
Iwamoto, Naoki
Fujikawa, Keita
Aramaki, Toshiyuki
Tamai, Mami
Nakamura, Hideki
Sato, Shuntaro
Origuchi, Tomoki
Kawakami, Atsushi - Abstract:
- Highlights: Early diagnosis and treatment of NPSLE are still difficult questions. The association between immunopathogenic aspects of NPSLE and outcomes has not been conducted. We were able to identify six minimum markers that can be used to predict outcomes. Measuring multiple cytokines may contribute to predict NPSLE therapeutic outcomes. Our findings may indicate the importance of making a diagnosis at an earlier phase for better therapeutic response. Abstract: Introduction: Neuropsychiatric systemic lupus erythematosus (NPSLE), a serious organ disorder with a variety of symptoms, has diverse therapeutic outcomes because of the variability of NPSLE manifestations. A comprehensive association study of NPSLE among clinical and immunopathogenic aspects and outcomes has not been conducted. Methods: We analyzed the laboratory data, NPSLE symptoms, and clinical outcomes at 1 yr post-treatment and the profiles of 27 cytokines, chemokines and growth factors in cerebrospinal fluid (CSF) samples using the Bio-Plex Human 27-plex panel from 28 NPSLE patients. Univariate and multivariable competing risks regression analyses were used to determine the predictive factors of clinical response. We also tried to predict the outcome of NPSLE by the 27 cytokines/chemokines/growth factors using a weighted-voting (WV) algorithm. Results: Of the two males and 26 females (92.9%), 16 were non-responders at 1 yr post-treatment; in the final model, the independent predictors of non-responders wereHighlights: Early diagnosis and treatment of NPSLE are still difficult questions. The association between immunopathogenic aspects of NPSLE and outcomes has not been conducted. We were able to identify six minimum markers that can be used to predict outcomes. Measuring multiple cytokines may contribute to predict NPSLE therapeutic outcomes. Our findings may indicate the importance of making a diagnosis at an earlier phase for better therapeutic response. Abstract: Introduction: Neuropsychiatric systemic lupus erythematosus (NPSLE), a serious organ disorder with a variety of symptoms, has diverse therapeutic outcomes because of the variability of NPSLE manifestations. A comprehensive association study of NPSLE among clinical and immunopathogenic aspects and outcomes has not been conducted. Methods: We analyzed the laboratory data, NPSLE symptoms, and clinical outcomes at 1 yr post-treatment and the profiles of 27 cytokines, chemokines and growth factors in cerebrospinal fluid (CSF) samples using the Bio-Plex Human 27-plex panel from 28 NPSLE patients. Univariate and multivariable competing risks regression analyses were used to determine the predictive factors of clinical response. We also tried to predict the outcome of NPSLE by the 27 cytokines/chemokines/growth factors using a weighted-voting (WV) algorithm. Results: Of the two males and 26 females (92.9%), 16 were non-responders at 1 yr post-treatment; in the final model, the independent predictors of non-responders were longer disease durations of SLE (odds ratio [OR]: 1.490, 95% confidence interval [CI]: 1.143–2.461, p = 0.0003) and patients with more than one NPSLE symptom types (OR: 15.14, 95% CI: 1.227–452.1, p = 0.0334). The pretreatment CSF interleukin (IL)-6, IL-10, interferon-gamma (IFN-γ) and tumor necrosis factor-alpha (TNF-α) levels were significantly higher in the non-responders ( p = 0.0207, p = 0.0054, p = 0.0242 and p = 0.0077, respectively). We identified six "minimum predictive markers:" IL-10, TNF-α, IL-6, IFN-γ, IL-4 and IL-13 by a WV algorithm that showed the highest accuracy (70.83%) and highest Matthews correlation coefficient (54.23%). Conclusions: We have devised a numerical prediction scoring system that was able to separate the non-responders from responders. The patients with longer disease durations of SLE and those with more than one NPSLE symptom types had poorer outcomes. Our findings may indicate both the importance of making a diagnosis at an earlier phase for better therapeutic response and the usefulness of measuring multiple cytokines to predict NPSLE therapeutic outcomes. … (more)
- Is Part Of:
- Cytokine. Volume 79(2016)
- Journal:
- Cytokine
- Issue:
- Volume 79(2016)
- Issue Display:
- Volume 79, Issue 2016 (2016)
- Year:
- 2016
- Volume:
- 79
- Issue:
- 2016
- Issue Sort Value:
- 2016-0079-2016-0000
- Page Start:
- 31
- Page End:
- 37
- Publication Date:
- 2016-03
- Subjects:
- AZA azathioprine -- b-FGF basic fibroblast growth factor -- CyA cyclosporine -- IVCY intravenous cyclophosphamide pulse -- MCC Matthews correlation coefficient -- mPSL pulse methyl prednisolone pulse therapy -- NPSLE neuropsychiatric systemic lupus erythematosus -- RTX rituximab -- SELENA–SLEDAI Safety of Estrogens in Lupus Erythematosus National Assessment–Systemic Lupus Erythematosus Disease Activity Index -- SLE systemic lupus erythematosus -- TAC tacrolimus -- WV weighted-voting
Systemic lupus erythematosus -- Neuropsychiatric systemic lupus erythematosus -- Multiple cytokine profiles -- Cerebrospinal fluid -- Weighted-voting algorithm
Cytokines -- Periodicals
571.844 - Journal URLs:
- http://www.sciencedirect.com/science/journal/10434666 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cyto.2015.12.010 ↗
- Languages:
- English
- ISSNs:
- 1043-4666
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3506.778000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 1899.xml