DOI 10.1016/j.jdermsci.2021.10.003
Clinical and laboratory parameters predicting cancer in dermatomyositis patients with anti-TIF1γ antibodies.
Аннотация
BACKGROUND
Dermatomyositis (DM) is a chronic acquired autoimmune disorder strongly associated with cancer development. Until now, identifying predictive markers indicating a high risk of cancer has challenged clinicians. Although anti-TIF1γ antibody is a major serological indicator for cancer-associated DM, many anti-TIF1γ antibody-positive DM patients lack malignancy.
OBJECTIVES
To determine clinical and laboratory parameters that support cancer prediction in anti-TIF1γ antibody-positive DM patients.
METHODS
Clinical and laboratory data were collected from cancer-associated and unassociated DM patients with anti-TIF1γ antibodies. Serum cytokine concentrations were measured with a cytokine array assay. The values of inflammatory cytokines in cancer prognosis were determined with a receiver operating characteristic curve analysis.
RESULTS
The cancer group had a significantly higher frequency of males, older mean age and higher anti-TIF1γ antibody levels. Some inflammatory cytokines, particularly tumour necrosis factor (TNF) and TNF receptor superfamilies, had increased levels in sera that were correlated with myositis markers, cutaneous severity and DM disease activity. Moreover, these cytokines had an area under the curve (AUC) ≥0.8 and high sensitivity and specificity at their specific cut-off, even higher than anti-TIF1γ levels in cancer prediction in our DM patients.
CONCLUSIONS
Our results suggest a close pathophysiological relationship among myositis, cancer and skin involvements in DM patients with anti-TIF1γ antibodies and the potential clinical significance of anti-TIF1γ antibody levels in evaluating disease severity and prognosis in DM patients. Some inflammatory cytokines, particularly TNF and TNF receptor superfamilies including BAFF, sTNF-R1 and sTNF-R2, may support cancer prediction in DM patients with anti-TIF1γ antibodies.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
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