Higher eosinophil-to-lymphocyte and neutrophil-to-lymphocyte ratios were observed in patients with severe alopecia areata up to 18 months prior to diagnosis, according to a recent study.
In the nationwide, retrospective cohort study, published in PLOS ONE, investigators examined hematologic ratios as potential biomarkers of alopecia areata (AA) severity. They analyzed data from 147,020 patients diagnosed with AA and 141,598 matched controls enrolled in Israel’s largest health maintenance organization. The investigators aimed to determine whether neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), eosinophil-to-lymphocyte ratio (ELR), eosinophil-to-neutrophil ratio (ENR), and eosinophil-to-monocyte ratio (EMR) correlated with disease severity.
The study included adult patients diagnosed with AA between 2005 and 2020 with complete blood count data available within 30 days of diagnosis. Exclusion criteria included recent infections, malignancies, or surgeries. Controls were matched by gender and birth year, with blood count data obtained within 1 year of their matched AA patient’s test. AA severity was classified based on treatment, with moderate-severe cases defined as those receiving systemic therapy or intralesional injections, whereas others were classified as mild.
Patients with AA exhibited significantly higher NLR and ELR values compared with controls (NLR: odds ratio [OR] = 1.02, 95% confidence interval [CI] = 1.01–1.03, P < .001; ELR: OR = 1.21, 95% CI = 1.05–1.39, P = .007). When stratified by severity, moderate-severe patients had higher NLR (OR = 1.11, 95% CI = 1.09–1.1, P < .001), PLR (OR = 1.09, 95% CI = 1.05–1.13, P < .001), ELR (OR = 2.06, 95% CI = 1.67–2.53, P < .001), and EMR (OR = 1.07, 95% CI = 1.03–1.07, P < .001) compared with mild cases. These trends were also observed 12 to 18 months prior to AA diagnosis.
Receiver operating characteristic curve analysis identified cut-off values for severe AA: NLR (1.87), PLR (126.36), ELR (0.09), EMR (0.59), and ENR (0.09), with area under the curve values ranging from 0.50 to 0.54. While statistically significant, the predictive accuracy of these biomarkers was modest. Although the associations between AA and these biomarkers were observed, their predictive accuracy was limited, highlighting the need to integrate both clinical and laboratory factors for a more comprehensive assessment. Additional research is needed to better define the sensitivity and specificity of these markers, particularly when used alongside other blood markers. These findings differed from previous literature and may offer a practical approach for assessing disease severity and progression.
Full disclosures can be found in the published study.
