Figure. Skindex-293 subscale scores for responders (A) and nonresponders (B). Illustrated are Emotions, Functioning, and Symptoms subscale scores obtained before and after treatment (Tx). Blue lines indicate mean score. Black lines connect data from before and after Tx for the same individual.
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Chang AY, Ghazi E, Okawa J, Werth VP. Quality of Life Differences Between Responders and Nonresponders in the Treatment of Cutaneous Lupus Erythematosus. JAMA Dermatol. 2013;149(1):104–106. doi:10.1001/2013.jamadermatol.467
Patients with cutaneous lupus erythematosus (CLE) have very poor quality of life.1 When compared with those with other skin diseases, patients with CLE are among those most severely affected by their condition. Psychologic aspects of quality of life in CLE are similar to, or worse than, what is experienced by patients with chronic hypertension, congestive heart failure, type 2 diabetes mellitus, and recent myocardial infarction. In considering this, we were interested in assessing whether patients who demonstrated response to treatment also experienced change to their quality of life.
This institutional review board–approved study prospectively evaluated response to systemic therapy in patients with CLE using the CLE Disease Area and Severity Index (CLASI)2 and the Skindex-29.3 The CLASI is a validated clinical tool that quantifies disease activity and damage separately, with higher scores indicating more severe disease. The Skindex-29 is a validated, skin-specific quality of life measure that calculates 3 subscale scores: Emotions, Functioning, and Symptoms, with higher scores indicating worse quality of life.3
Eligible patients met modified Gilliam criteria4 for CLE and had at least 2 visits during which CLASI and Skindex-29 scores were measured. Patients with a diagnosis of systemic lupus erythematosus (SLE) were included. Details regarding the identification of eligible patients have been discussed previously.5 From among the eligible patients, those who had been initiated on antimalarial therapy (hydroxychloroquine, hydroxychloroquine-quinacrine, chloroquine, or chloroquine-quinacrine) or antimetabolite therapy (methotrexate, mycophenolate, or azathioprine) were identified. Twenty-seven patients were initiated on antimalarial therapy. Hydroxychloroquine was dosed at 200 to 400 mg/d, and chloroquine was dosed at 250 mg/d for 5 to 7 days per week, based on ideal body weight. Quinacrine was dosed at 100 mg/d. Twelve patients were initiated on antimetabolite therapy. Antimetabolite treatment was initiated at a low dose, and the dose was increased until the lowest effective and tolerated dose was achieved. The median (interquartile range [IQR]) dose for methotrexate was 13.8 (10.6-16.3) mg/wk; for mycophenolate, it was 2000 (1750-2500) mg/d; for azathioprine, 100 (75-125) mg/d. For 6 of 39 patients included in this study, data were available for initiation of two systemic therapies. In these cases, data from the first therapy that was initiated were included, and the remainder were excluded.
Consistent with previous work,5,6 response was defined as either a 4-point or 20% decrease in CLASI activity score and determined by comparing the score at the pretreatment visit with the first posttreatment visit. The first posttreatment visit occurred at least 2 months following the pretreatment visit. For patients with more than 1 posttreatment visit, the first posttreatment visit was used. All responders and nonresponders were pooled together, regardless of which systemic therapy was initiated, and Skindex-29 subscale scores were compared between the pretreatment visit and the first posttreatment visit.
Skindex-29 subscale scores were normally distributed, and paired t tests were used. Spearman correlation tests were performed between change in Skindex-29 subscale score and change in CLASI activity score. Stata software, version 11.0 (StataCorp LP) and GraphPad Prism, version 5.0 (GraphPad Software Inc) were used for data analysis.
For 23 responders of 39 patients initiated on an antimalarial or antimetabolite therapy, the mean (95% CI) Emotions score decreased from 53.9 (40.6-67.1) to 38.8 (28.2-49.4) (P = .002); Functioning score decreased from 32.7 (20.5-44.9) to 20.9 (13.1-28.7) (P = .01); and Symptoms score decreased from 47.2 (37.8-56.6) to 33.7 (26.6-40.8) (P < .001) (Figure, A). For the 16 nonresponders, the mean (95% CI) Emotions, Functioning, and Symptoms scores were unchanged: 48.0 (33.3-62.7) to 53.0 (38.3-67.6) (P = .30); 25.1 (13.2-37.1) to 25.1 (13.2-37.1) (P > .99); and 44.2 (32.4-56.0) to 43.0 (28.1-57.8) (P = .81), respectively (Figure, B). Differences in pretreatment CLASI scores, duration between visits, diagnosis (CLE only vs CLE and SLE), age, sex, and smoking status between responders and nonresponders were not statistically significant. Change in CLASI activity score was correlated with change in Skindex-29 subscale scores: Emotions, r = 0.39 (P = .01); Functioning, r = 0.29 (P = .07); and Symptoms, r = 0.33 (P = .04).
Response in disease activity was accompanied by an improvement in skin-specific quality of life measures. Correlation analysis suggests that disease activity is not the only factor influencing quality of life. The impact of treatment adverse effects on quality of life is unaccounted for in this study because various medications were used. Larger studies of systemic therapies in CLE that focus on quality of life and its contributory factors are needed.
Correspondence: Dr Werth, Department of Dermatology, Perelman Center for Advanced Medicine, 3400 Civic Center Blvd, Ste 1-330S, Philadelphia, PA 19104 (firstname.lastname@example.org).
Accepted for Publication: July 26, 2012.
Author Contributions: Drs Chang and Werth had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Chang, Ghazi, and Werth. Acquisition of data: Chang, Ghazi, Okawa, and Werth. Analysis and interpretation of data: Chang and Werth. Drafting of the manuscript: Chang. Critical revision of the manuscript for important intellectual content: Chang, Ghazi, Okawa, and Werth. Statistical analysis: Chang and Werth. Obtained funding: Chang and Werth. Administrative, technical, and material support: Ghazi and Werth. Study supervision: Okawa and Werth.
Financial Disclosure: None reported.
Funding/Support: This study is based on work supported by the Doris Duke Charitable Foundation (Dr Chang) and the National Institutes of Health, grant NIH K24-AR 18 02207 (Dr Werth).
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