Objectives: In the present study, inflammatory factors, including interleukin (IL) and tumor necrosis factor-α (TNF-α) in the peripheral blood of patients with sporadic amyotrophic lateral sclerosis (sALS), were evaluated, and the issue of whether these variables were associated with the progression and severity of the disease examined. Methods: Data on inflammatory factors, including IL-1, IL-2, IL-6, IL-8, IL-10, and TNF-α, were retrospectively collected from 248 sALS patients admitted to the Chinese PLA General Hospital between March 2018 and March 2021. The relationships between the variables and clinical features, including gender, age at onset, site of onset, time from onset to hospital admission, ALS functional rating scale score, and diagnostic category were analyzed. Results: IL-1, IL-2, IL-6, IL-8, IL-10, and TNF-α levels were elevated in 43.75%, 7.04%, 16.42%, 25.35%, 1.41%, and 50.72% of ALS patients, respectively, compared with the normal value range. IL-2 and IL-6 levels were inversely associated with the ALS functional rating scale score (r = −0.280, p = 0.004 and r = −0.198, p = 0.048). Conclusion: Elevated levels of inflammatory cytokines support the hypothesis of an inflammatory response in ALS, and IL-2 and IL-6 may be used as an inflammation-related biomarker for disease severity.

Objectives: To analyze the factors affecting prognosis of patients with sporadic amyotrophic lateral sclerosis (ALS), to establish a nomogram predictive model. Methods: A total of 236 patients with sporadic ALS hospitalized in the Department of Neurology of the First Medical Center, Chinese PLA General Hospital, from March 2011 to November 2021 were enrolled in the study. Basic information and clinical and laboratory data of patients were collected, including sex, age at onset, body mass index, disease duration, diagnostic grade, and serum levels of creatine kinase (CK), creatinine (Cr), uric acid (UA), and ferritin. Kaplan-Meier univariate and multivariate Cox proportional hazard regression models were used to analyze the prognostic factors, and a nomogram predictive model was established. Results: Univariate analysis showed that ferritin, CK, Cr, age at onset, disease duration, and body mass index (BMI) were all correlated with prognosis of ALS. Multivariate analysis showed that ferritin, Cr, disease duration, age at onset, and BMI were the strongest predictors. ROC curve and correction curve analyses verified the accuracy of the nomogram prediction model. Conclusions: Ferritin, Cr, disease duration, age at onset, and BMI are independent predictors of survival in patients with ALS. Based on these clinical and biological prognostic factors, we established a quantitative model for predicting survival probability, and may assist in the prognostic evaluation of ALS, pending further validation.